Hot topic: New pharmacological tools reiterate lack of direct connection between Angiotensin 1–7 and the MAS1 GPCR

A new type of deorphanization conundrum confronted in pairing the GPCR, MAS1 with the hormonal peptide angiotensin 1–7 (Ang1-7) was emphasised in recent IUPHAR reviews (1, 2). More evidence for disconnection between Ang1-7 and MAS1 is presented in the recent paper by Gaidarov et al. (3). Ang1-7 is produced by ACE2 or neutral endopeptidase by cleavage of a single amino acid, phenylalanine 8, from angiotensin II (AngII), the major renin angiotensin system hormone. MAS1 was described as the primary receptor for Ang1-7 in regulating diverse biological activities, including vasodilatory, cardio-protective, antithrombotic, antidiuretic and antifibrotic effects (4). These activities are lost in tissues of MAS1-deficient animals, producing striking phenotypes observed in the cardiovascular, renovascular, nervous and reproductive systems. Vast physiological responses to Ang1-7 studied in MAS1-deficient animals serve as the most compelling argument in favor of Ang1-7 pairing with MAS1. However, support for a direct interaction of Ang1-7 with MAS1 lack demonstration of classical G protein signaling and desensitization response to Ang1-7, as well as a lack consensus on confirmatory molecular pharmacological analyses (1, 2).

MAS1-selective small molecule agonists and antagonists from Arena Pharmaceuticals have aided mechanistic study of signaling dynamics in recombinant MAS1 expressing cells. Gaidarov et al. systematically tested efficacy of MAS1-selective non-peptide agonists and antagonists in GPCR signaling and also in signaling-pathway independent assay platforms [3]. Arena Pharmaceutical’s non-peptide ligands modulated G protein-dependent and independent pathways through MAS1, including Gq and Gi pathways, 35S-GTPɣS binding, β-arrestin recruitment, Erk1/2 and Akt phosphorylation, arachidonic acid release, and receptor internalization. Moreover, non-peptide agonists produced robust responses in dynamic mass redistribution (DMR) assays that provide a pathway-agnostic cellular response. The Ang1-7 peptide obtained from multiple sources was inert. In the cell-free assay for G protein coupled MAS1, 35S-GTPɣS binding was undetected in the presence of Ang1–7 suggesting lack of direct interaction with MAS1.

To reject the in vivo analysis based MAS1 pairing with Ang1-7 would still be premature based on the conclusions of Gaidarov et al. (and similar papers cited in ref. #2). MAS1 pairing with Ang1-7 should be considered in the context of type 1 and type 2 errors originally described by Neyman and Pearson (5) and recently revisited (6). Type 1 errors are experiments causing rejection of a null hypothesis which may be true. Type 2 errors are experiments insufficient to reject a flawed null hypothesis. Experiments need to be designed to test the validity of MAS1 functions modulated in vivo by Arena Pharmaceutical ligands rather than simply failing to find pairing with Ang1-7. Involvement of additional GPCRs as “Ang1-7 receptors” or signalosome mechanisms that can link Ang1-7 with MAS1 deserve consideration (7).

Comments by Sadashiva S. Karnik (karniks@ccf.org.us) and Kalyan Tirupula

References

  1. Karnik SS, Singh KD, Tirupula K, Unal H. (2017) Significance of angiotensin 1-7 coupling with MAS1 receptor and other GPCRs to the renin-angiotensin system: IUPHAR Review 22. Br J Pharmacol. 174: 737-753. doi: 10.1111/bph.13742. Review. PMID: 28194766
  2. Karnik SS, Unal H, Kemp JR, Tirupula KC, Eguchi S et al. (2015) International Union of Basic and Clinical Pharmacology. XCIX. Angiotensin Receptors: Interpreters of Pathophysiological Angiotensinergic Stimuli [corrected]. Pharmacol Rev 67: 754-819. PMID: 26315714
  3. Gaidarov I, Adams J, Frazer J, Anthony T, Chen X et al. (2018) Angiotensin (1-7) does not interact directly with MAS1, but can potently antagonize signaling from the AT1 receptor. Cell Signal 50: 9-24. PMID: 29928987
  4. Bader M, Alenina N, Andrade-Navarro MA, Santos RA (2014). MAS and its related G protein-coupled receptors, Mrgprs. Pharmacol Rev. 66: 1080–1105. PMID: 25244929
  5. Neyman, J. and Pearson, E.S. (1928). On the use and interpretation of certain test criteria for the purposes of statistical inference. Part I and Part II. Biometrika 20A, 175–240.
  6. Lew MJ (2006). Principles: when there should be no difference–how to fail to reject the null hypothesis. Trends Pharmacol Sci. 27:274-278. PMID: 16595154
  7. Tirupula KC, Zhang D, Osbourne A, Chatterjee A, Desnoyer R, Willard B et al. (2015). MAS C-terminal tail interacting proteins identified by mass spectrometry-based proteomic approach. PLoS One 10: e0140872. PMID: 26484771
Posted in Hot Topics

Hot Topic: Structural details for coupling of the agonist-occupied µ opioid receptor (amongst others) to the Gi protein

Every few years in the field of receptor pharmacology, a technological advance occurs that drives the field forward in terms of insight and understanding. Over the past couple of years, the cryo-EM technique (the development of which won the 2017 Nobel Prize in Chemistry for Dubochet, Frank, and Henderson) for resolving protein structures at near atomic resolution has been highlighted as one such approach. Now some of the first papers applying this methodology to G protein-coupled receptors (GPCRs) are beginning to appear. The strength of this approach for GPCRs is revealed in the recent paper by Koehl et al. (1) showing the detailed structure of the agonist-bound µ opioid receptor (GtoPdb target ID 139) coupled to the Gi subtype of G protein. DAMGO (GtoPdb ligand ID 1647), the agonist used in the study, is a selective and efficacious peptide agonist at the µ receptor and is used in many studies as the standard µ receptor agonist. The structure of the DAMGO-µ receptor-Gi complex shows some interesting and unexpected detail, for example, that the binding pocket for Gi at the base of the receptor is smaller, and the outswing of the lower end of TMD VI smaller, than that for GPCRs that couple primarily to Gs proteins.

Apart from the obvious benefits for future drug development at µ receptor, the full impact of the cryo-EM approach for µ receptor structure/function is likely to be felt more in the future, as we can no doubt look forward to the appearance of µ receptor/signalling protein structures with partial agonists as well as biased agonists, and the structure of ligand-bound µ receptor interacting with GRKs or arrestin proteins. The speed at which this field is moving is already breathtaking – in the issue of Nature carrying the DAMGO-µ receptor-Gi cryo-EM report, there are others detailing the structure of activated rhodopsin-Gi (2), adenosine activated adenosine A1-Gi (3) and agonist-activated 5HT1B-Go (4). Recently also the structure of the Class B GLP-1 receptor in complex with a biased ligand and Gs was reported (5). Many more structures of such complexes are likely to follow over the next couple of years, with a corresponding leap forward in our understanding of the structure and function of GPCRs. There are still challenges however; as Koehl and colleagues point out in their groundbreaking paper (1), the nature of the initial interactions of G proteins and other signalling proteins with GPCRs, and the identity of the possibly novel receptor conformations that exist at these early time points in complex formation, remain considerable challenges for both X-ray crystallography and cryo-EM techniques.

Comments by Eamonn Kelly (E.Kelly@bristol.ac.uk) and Katy Sutcliffe

(1) Koehl A. et al. (2018). Structure of the μ-opioid receptor–Gi protein complex. Nature, 558. 547–552. [PMID: 29899455]

(2) Kang Y. et al. (2018). Cryo-EM structure of human rhodopsin bound to an inhibitory G protein. Nature, 558. 553-558. [PMID: 29899450]

(3) Draper-Joyce C.J. et al. (2018). Structure of the adenosine-bound human adenosine A1 receptor–Gi complex. Nature, 558. 559–563. [PMID: 29925945]

(4) García-Nafría J. et al. (2018). Cryo-EM structure of the serotonin 5-HT1B receptor coupled to heterotrimeric Go. Nature, 558. 620-623. [PMID: 29925951]

(5) Liang Y.L. et al. (2018). Phase-plate cryo-EM structure of a biased agonist-bound human GLP-1 receptor-Gs complex. Nature, 555. 121-125. [PMID: 29466332]

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Posted in Hot Topics

Hot Topic: Systems Medicine, Disease Maps and the future of Systems Biology

What will Systems Biology look like in the future? Up to now, it has focussed on the development of standards, software tools and databases that enabled us to study the dynamics of physiological function mechanistically. However as these tools and technologies have matured, the focus of the systems biology research community has moved towards how they can best be interconnected and exploited to develop our understanding of health and disease across whole cells, tissues, organs, organisms. This version 2.0 of systems biology, will build on the existing technologies to create resources that are more intuitive, more accurate, more accessible and are easier to use for anyone engaged with research.

Disease maps describe the interactions and pathways that are perturbed from healthy physiological function in disease pathophysiology. The Disease Maps consortia, spearheaded by the Luxembourg Centre for Systems Biomedicine, the Institut Curie and the European Institute for Systems Biology and Medicine, are developing rich resources to enable us to understand how healthy function is perturbed across different scales. These include from the molecular to the organismal, and that embed individually perturbed pathways in a wider intra- and inter-cellular network so that the systems and systemic impact can be more easily investigated [1].   Each disease topic is the focus of a community of clinical, laboratory and systems biology expertise and the consortia is organised as a community of communities with the following adopted principles:-

  • Central integration of in vivo and in vitro disease experts across diseases
  • Close integration of pathway mapping and modeling expertise
  • Regular sharing of best practice and expertise across diseases

The consortia embrace open access, standard formats, modularity, consistency of quality and best practices in the field. It is anticipated that this work will deliver resources that can support comprehensive programmes of systems medicine by including the following:

  • Dedicated trusted reference resources describing disease mechanisms that facilitate advanced data interpretation, hypothesis generation, and hypothesis prioritisation.
  • Tools for the study of co- and multi-morbidities, which can deliver refined biomarkers for improved clinical diagnostics.
  • Tools for the study of systems pharmacology that suggest drug repositioning and multi-drug intervention strategies.
  • Novel insights into disease subclassification supporting the development of next-generation disease ontologies.
  • Supporting the design and prototyping of new clinical decision-making strategies.

The Disease Maps consortia thus want to accelerate the development of Systems Biology 2.0 and the roadmap presented in this paper describes how it can be steered towards translational utility.

Comments by Steven Watterson (@systemsbiology), University of Ulster

[1]. Mazein A, Ostaszewski M, Kuperstein I, Watterson S, Le Novère N, Lefaudeux D, De Meulder B, Pellet J, Balaur I, Saqi M, Nogueira MM, He F, Parton A, Lemonnier N, Gawron P, Gebel S, Hainaut P, Ollert M, Dogrusoz U, Barillot E, Zinovyev A, Schneider R, Balling R and Auffray C (2018) Systems medicine disease maps: community-driven comprehensive representation of disease mechanisms, NPG Systems Biology and Applications 4:21. [PMID 29872544]

Posted in Hot Topics

Hot topic: Structure of the adenosine-bound human adenosine A1 receptor–Gi complex

The A1 adenosine receptor is, for most people, a molecular target they can become conscious of when they block it, which happens frequently. Rapid consumption of higher doses of caffeine, in products like Italian espresso or Turkish coffee, provokes a rapid, transient increase in heart rate and a noticeable increase in limb tremor. As the most widely consumed psychoactive substance, caffeine has these effects through blockade of the A1 adenosine receptor, which is found on cardiomyocytes and the peripheral nerve terminals of the sympathetic nervous system (as well as many other locations), leading to an increase in cardiac contractility and noradrenaline release, respectively.

In this report, a 3.6 Å structure of the receptor complexed with the endogenous agonist, adenosine, in the presence of the heterotrimeric G12 protein has been resolved by cryo-EM. As expected, there are differences in conformation compared to the previously-reported antagonist-bound receptor, principally in TM1 and TM2. There are also differences compared to the structure reported for the Gs-coupled, agonist-bound beta2-adrenoceptor.

Comments by Steve Alexander (@mqzspa)

(1) Draper-Joyce C.J. et al. (2018). Structure of the adenosine-bound human adenosine A1 receptor–Gi complex. Nature, 558. 559–563. [PMID: 29925945]

Posted in Hot Topics

Database release 2018.3

Our third database release of the year, 2018.3, is now available. This update contains the following new features and content changes:

Content updates

GPCRs:
Adenosine receptors
Chemokine receptors
Cholecystokinin receptors
Dopamine receptors
Ghrelin receptors
Opioid receptors
GPR55 receptors

NHRs:
MRetinoic acid receptor

Channels:
Transient Receptor Potential channels
voltage-gated sodium channels

Enzymes:
Guanylyl cyclases (GCs)
Janus kinase (JakA) family
Mitogen-activated protein kinases (MAP kinases)
Nitric oxide synthases

Catalytic Receptors:
Natriuretic peptide receptor family

Transporters:
ABCG subfamily
Monoamine transporter subfamily

Others:
CD molecules

Anti-malarial data

The existing Antimalarial targets family has been updated with 5 new P. falciparum (3D7) targets:

  • PfATP4 (Plasmodium falciparum ATPase4)
  • PfDHFR-TS (Plasmodium falciparum bifunctional dihydrofolate reductase-thymidylate synthase)
  • PfDXR (Plasmodium falciparum 1-deoxy-D-xylulose 5-phosphate reductoisomerase)
  • PfeEF2 (Plasmodium falciparum elongation factor 2)
  • PfPI4K (Plasmodium falciparum phosphatidylinositol 4-kinase)

A new Antimalarial ligands family has been created and contains 30 ligands all tagged as an antimalarial in the database. Of these 30, 20 are new ligands curated for this release.

New website features

GtoImmuPdb now public

The IUPHAR Guide to IMMUNOPHARMACOLOGY is now at its first public release and is no longer considered a beta version. We will continue to develop the portal and specific immuno interfaces as well as continuing curation towards its official launch in October 2018. This will be at the BPS Immunopharmacology: Challenges, opportunities and research tools meeting in Edinburgh, 1st-2nd October 2018.

Disease Summary Pages

The disease summary pages have been modified to improve the payout of target information and provide links to help to understand terms and symbols. The display of associated ligand is now in a sortable table and the comments section includes bioactivity comments where present. We have also include links to the specific clinical data or bio-activity tabs on ligand summary pages.

Posted in Database updates, Guide to Immunopharmacology, Guide to Malaria Pharmacology

Commentary on the distinction between Cannabis and cannabinoids

The Cannabis plant is a natural product from which more than 100 apparently unique metabolites (cannabinoids) have been identified. Many of these have been found in human plasma following consumption of Cannabis preparations. The most well-recognised is tetrahydrocannabinol, THC, because of its well-documented psychotropic effects mediated through activating CB1 cannabinoid receptors. It has been used clinically as an anti-emetic and for treating glaucoma.

Cannabidiol, CBD, is also a prominent metabolite from the plant, which lacks the psychotropic effects of THC, since it is not an agonist at CB1 cannabinoid receptors. It is in advanced trials for treating childhood epilepsy, but may also have benefit in schizophrenia or post-traumatic stress disorder. The molecular mechanisms of action of CBD are not precisely defined, but may involve multiple targets.

A standardised combination of THC and CBD is available in many countries, including the UK as a licensed medicine for treating the symptoms of multiple sclerosis.

There is a lack of clear understanding of the biological effects of the majority of the other cannabinoid metabolites from the plant, which may have applications in inflammatory disorders, nausea and metabolic disorders, such as type II diabetes.

In many countries, Cannabis itself is licensed as a medicine for indications such as pain relief or the weight loss associated with terminal cancer or AIDS. However, preparations from Cannabis are highly variable in terms of the spectrum and concentrations of cannabinoid content, as well as other compounds present in the plant, such as the terpenoids, which have also been proposed to have independent bioactivity.

Commentary by Steve Alexander (@mqzspa) & Anthony Davenport

Posted in Hot Topics, Uncategorized

GtoPdb: Database Status Reports

As some of our contacts may know, we hold hemi-annual meetings between IUPHAR, BPS the GtoPdb team, together with invited guests from our collaborators and NC-IUPHAR committee representatives. Covering ~ 2.5 days these usually take place in Paris or Edinburgh. One of the outputs from these rewarding gatherings is an extensive (i.e. ~ 20-25 pages) database report document. For interested parties these provide a usefully detailed snapshot of what we have collectively been up to for the preceding 6-month period.

The last three of these are now on-line (http://www.guidetopharmacology.org/download.jsp#db_reports).

The latest one (May 2018) also includes links to slide sets shown in the meeting that accompany the report, which are also available here:

Database Status Report: Core GtoPdb

Database Status Report: GtoImmuPdb

Linking GtoPdb, PubChem and PubMed

 

Posted in Database updates, Technical, Uncategorized

Hot topic (update): from double to triple whammy for BACE1 inhibitors

19 June 2018 update. Announced only about a week after the events described below,  yet a third clinical candidate, lanabecestat  (AZD-3293, LY3314814) has also bitten the dust (4).  The two PhIII trials were stopped because they were deemed unlikely to meet their primary endpoints. This bad news engendered yet another “In The Pipeline” commentary  If detailed reports are eventually published these will be curated as new references for the ligand entry.

*********************************

BACE1  (beta secretase 1, BACE-1 or BACE) has been a key target for Alzheimer’s disease (AD) for nearly two decades (1).  However, there was a major disappointment when the Phase III trials with the Merck inhibitor verubecestat failed unequivocally despite lowering A-beta levels.  The termination is reported both in NCT01739348  and the  May 2018  full paper on the trial results (2).  The gravity of this setback is underlined by the “In The Pipeline” commentary title “Merck’s BACE-Inhibitor Alzheimer’s Wipeout” wherein it is suggested that this brings the validation status of this target and, by definition, other inhibitors in late-stage development into doubt.  Thus, even glimmers of success for any mechanistic class of AD  therapy would seem to be currently extinguished.   There remains perhaps the slimmest of hopes from the recent report that the initial process of plaque formation might yet prove sensitive to therapeutic BACE1 inhibition (3).  However, there may be no diagnostic and/or biomarker specific enough to identify prospective asymptomatic patients this early in disease development.

The bad news for BACE1 inhibitors was compounded by a press release from Janssen in the same month. They reported serious liver enzyme elevations for some participants in Janssen’s atabecestat  (JNJ-54861911) Phase 2b/3 trial.  While this may be a chemotype liability for this series rather than a target-related issue, it does mean that yet another AD drug candidate has bitten the dust.  We would hope that a full clinical data report on this trial cessation could be pending,  However,  despite a number of early clinical reports, Janssen has not so far published any primary in vitro medicinal chemistry papers on this compound.  Comments about both these failures have also just  appeared in Nature Reviews in Drug Discovery

N.b. Our BACE1  target entry is in the process of being updated so a number of new inhibitors and curatorial comments will appear in database release 2018.3.  The technicalities of gathering these new structures, including unblinding JNJ-54861911, as well as what might still be progressing,  are described in this blog post.

Comments by Chris Southan (@cdsouthan)

1) Southan and Hancock  (2013) A tale of two drug targets: the evolutionary history of BACE1 and BACE2. Front Genet. Dec 17;4:293. doi: 10.3389/fgene.2013.00293.[PMID 24381583]

2) Egan et. al.  (2018)  Randomized Trial of Verubecestat for Mild-to-Moderate Alzheimer’s Disease. N. Engl. J. Med., 378 (18): 1691-1703, [PMID 29719179]

3) Peters et. al. (2018) BACE1 inhibition more effectively suppresses initiation than progression of β-amyloid pathology, Acta Neuropathol. May;135(5):695-710. doi: 10.1007/s00401-017-1804-9. [PMID 29327084]

4) Update on Phase 3 Clinical Trials of Lanabecestat for Alzheimer’s Disease (2918)  Eli Lilly and AstraZeneca press release [CUL 14602932]

Posted in Hot Topics

Database release 2018.2

Our second database release of the year, 2018.2, is now available. This update contains the following new features and content changes:

Content updates

GPCRs:
5-Hydroxytryptamine receptors
Adenosine receptors
Adrenoceptors
Histamine receptors
Opioid receptors
Lysophospholipid (S1P) receptors
Prostanoid receptors

NHRs:
Mineralocorticoid receptor
Peroxisome proliferator-activated receptors

Channels:
Transient Receptor Potential channels
Nav1.5

Enzymes:
Nitric oxide synthases
Cyclooxygenase
Phosphodiesterases, 3′,5′-cyclic nucleotide (PDEs)
Cyclin-dependent kinase (CDK) family
Mitogen-activated protein kinases (MAP kinases)
NADPH oxidases

Transporters:
Monoamine transporter subfamily

Others:
Heat shock proteins

New website features

Pharmacology Search Tool

In release 2018.1 we announced a new Pharmacology Search Tool allowing users to upload lists of target ids and find ligands to modulate them. We have now extended this tool to (optionally) search for other relevant ligands in ChEMBL v23. The ChEMBL data has been filtered according to the same rules we use for the ligand activity visualisation charts (see the help documentation for details) and as well as displaying the ChEMBL curated activity values, we also display their calculated -log pChEMBL value. An example of the results returned from this type of search is shown in Fig 1.

pharm_search_res

Figure 1. Example of results returned from a UniProt Accession search in the Pharmacology Search Tool, showing the top 3 GtoPdb and ChEMBL ligands. Results are ordered by total number of ligands in these databases that match search criteria.

New PDB ligand icon

As part of our increased emphasis on ligand structures (as seen with our synPHARM resource), we have introduced a new ligand icon for PDB entries. We display this on the ligand list and target interaction tables to indicate which ligands have PDB entries (orange circle with a white alpha helix across the centre), as shown in Fig 2.

PDB_icon_lig_list

Figure 2A. The ligand list showing the new PDB ligand icon in orange.

PDB_object_icon

Figure 2B. A target inhibitor table showing the new PDB ligand icon in orange.

Sponsored Tocris product links

We have collaborated with Tocris as a quality supplier of many of the ligands in GtoPdb by adding links from our ligand pages out to the matching Tocris products. An example, which can be found on the ligand page beneath the summary tab, is shown in Fig 3. In total there are links to 1198 Tocris products.

tocris_link

Figure 3. Ligand summary page showing a link to the Tocris product.

Other updates

BJP/BJCP linking

As an adjunct to our successful entity-linking initiative for the BJP and more recently BJCP, we have instigated a process whereby, on manuscript acceptance and their own marking-up of GtoPdb links, authors alert us directly to key entities from their studies that are not in our database. In most cases, we then add the missing ligands. This has the advantages for both the author and the journal of not only adding their reference into GtoPdb but also the paper gains PubChem PubMed reciprocal linking derived from our PubChem ligand submissions. Examples from this release include GS-458967 from BJP and esaxerenone from BJCP.

BACE1 in doubt as an Alzheimer’s drug target

The target entry for the Alzheimer’s drug target BACE1 underwent key updates. The first of these was to add a new reference for the full report published just last week on the Phase III failure of the lead Merck BACE1 inhibitor verubecestat. Unfortunately, this paper now casts doubt on the target validation status and thus the future for this entire class of compounds pursued intensively for over 18 years. Notwithstanding, several ligands on the BACE1 list may yet complete their clinical evaluation (these will be joined by the latest  development candidate from Pfizer as PF-06751979 in 2018.3)

SynPHARM article

We are pleased to report that an open pre-print version (i.e. pending changes compared to the eventually accepted journal version) of our manuscript describing our SynPharm resource is now on-line.

How-to-Guide 

We are also pleased to report the publication of  Accessing Expert‐Curated Pharmacological Data in the IUPHAR/BPS Guide to PHARMACOLOGY. It is not indexed in PubMed yet but note that the PDF is free to access until the end of May (so pull it down while you can! – but we could send you one if you miss the window).  It includes useful examples of how to use both GtoPdb and GtoImmuPdb as a supplement to our online help and FAQ.

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Posted in Database updates, Guide to Malaria Pharmacology

Hot topic: Cryo-EM structure of the adenosine A2A receptor coupled to an engineered heterotrimeric G protein

The A2A adenosine receptor is densely expressed in dopamine-rich areas of the brain and in the vasculature. It is the target of an adjunct medication for Parkinson’s Disease, istradefylline in Japan, an A2A receptor antagonist.

The A2A adenosine receptor is an example of a Gs-coupled receptor, activation of which in the cardiovascular system leads to inhibition of platelet aggregation and vasorelaxation. This new report (1) highlights the link between the receptor and the G protein to focus on areas of unexpected flexibility in the ligand binding region. Further, classical understanding of receptor:G protein interaction identifies a prominent role for the third intracellular loop and the proximal end of the C-terminus (in some GPCR, such as the beta2-AR, a fourth intracellular loop is formed by palmitoylation of an intracellular cysteine residue, which the A2A lacks). The model generated from this cryo-EM study with a nanobody suggests a potentially novel role for an interaction between the first intracellular loop and the Gbeta subunit.

Comments by Steve Alexander (@mqzspa)

(1) Garcia-Nafría J et al. (2018). Cryo-EM structure of the adenosine A2A receptor coupled to an engineered heterotrimeric G protein. eLife, 7. pii: e35946. doi: 10.7554/eLife.35946. [PMID: 29726815]

Posted in Hot Topics

Hot topic: Conformational plasticity in the selectivity filter of the TRPV2 ion channel

The TRPV2 ion channel is the less well-characterised relative of the TRPV1 or vanilloid receptor that is activated by capsaicin. TRPV2 channels have many similarities to the TRPV1 channels, in that they are homotetrameric and respond to some of the same ligands (natural products such as cannabinoids) as well as being triggered at elevated temperatures. This study (1) focusses on a different common feature of the whole Transient Receptor Potential family, which are often described as non-selective cation channels. Using comparative analysis of crystals structures in which calcium is bound with and without an agonist, resiniferatoxin, present. The authors suggest that this agonist evokes a symmetrical opening of a selectivity filter gate, which permits increased permeation of calcium ions and also larger organic cations, such as the dye Yo-PRO-1.

Comments by Steve Alexander (@mqzspa)

(1) Zubcevic L et al. (2018). Conformational plasticity in the selectivity filter of the TRPV2 ion channel. Nat Struc Mol Biol., 25:405-415. doi:10.1038/s41594-018-0059-z. [Abstract]

Posted in Hot Topics

Hot topic: 3D structure of the P2X3 receptor bound to a negative allosteric modifier, identifies a binding site that is a target for development of novel therapeutic agents

Negative allosteric modulators (NAMs) are of great interest in drug development because they offer improved scope for the production of receptor antagonists with enhanced subtype-selectivity. Indeed, many NAMs are already on the market or undergoing clinical trials. NAMs act by binding to sites within receptors that are distinct from the primary, orthosteric ligand binding site and can inhibit the structural rearrangements of a receptor that are induced by orthosteric agonist binding.

P2X receptors are ligand-gated cation channels for which ATP is the endogenous orthosteric agonist. They are expressed throughout the body and the evidence indicates that they have numerous functions, including in sympathetic and parasympathetic neurotransmission, perception of sound, taste and pain, and immune regulation. Seven P2X subunits have been identified, which form trimers, to produce at least twelve different receptor subtypes. A major issue within the field has been a lack of selective antagonists for most P2X subtypes. This is unsurprising given the amino acid sequence similarity within the ATP binding site. Several selective NAMs have now been developed, but little is known about where in receptors they act and how exactly they inhibit receptor activation.

AF-219 is small molecule NAM at P2X3 receptors that was reported to be effective in a phase II clinical trial for treatment of refractory chronic cough. Wang et al., (1) combined X-ray crystallography, molecular modelling, and mutagenesis, to identify the site and mode of action of AF-219. P2X3 receptors are composed of three subunits, each of which adopts a conformation that could be likened to the shape of a leaping dolphin. The tail represents the transmembrane-spanning regions, the upper body the bulk of the extracellular loop and the head the most distal part of the extracellular loop. Also attached to the body are three structurally-distinct elements: the dorsal fin, the right flipper, and the left flipper. As a trimer, the subunits wrap round each other to produce a structure that resembles a chalice.

The AF-219 binding site is formed by the lower body and dorsal fin of one subunit and the lower body and left flipper of an adjacent subunit. Mutational analysis identified which amino acid residues within this pocket are essential for AF-219 binding, whilst in silico modelling showed that the small molecule P2X3 NAMS, AF-353, RO-51, RO-3 and TCP 262, but not the large NAMS suramin and PPADS, also bind to the same site. Activation of P2X3 receptors by ATP closes the binding cavity, so by occupying it, AF-219 prevents the protein structural rearrangements that lead to opening of the P2X3 receptor ion pore.

This identification of the AF-219 NAM binding site in P2X3 receptors is an opportunity for rational, intelligent drug design. It enables virtual screening of compound libraries, with the aim of identifying potential new molecular core structures, which can then be modified in order to optimise the structure of a novel NAM. In addition, this site differs among P2X receptor subtypes, so it is highly possible that drugs with greatly enhanced subtype-selectivity can be developed.

Comments by Dr. Charles Kennedy, University of Strathclyde

(1) Wang J, Wang Y, Cui WW, Huang Y, Yang Y, Liu Y, Zhao WS, Cheng XY, Sun WS, Cao P, Zhu MX, Wang R, Hattori M, Yu Y. (2018). Druggable negative allosteric site of P2X3 receptors. Proc Natl Acad Sci U S A. 2018 pii: 201800907. doi: 10.1073/pnas.1800907115. [PMID:  29674445]

Posted in Hot Topics

Hot topic: 3D structures of the closed acid-sensing ion channel (ASIC) shed light on the activation mechanism of these neuronal ion channels

ASICs are potential drug targets of interest. Their activation mechanism has however remained elusive. ASICs are neuronal, proton-gated, sodium-permeable channels that are expressed in the central and peripheral nervous system of vertebrates. They form a subfamily of the Epithelial Na channel / degenerin channel family, and contribute to pain sensation, fear, learning, and neurodegeneration after ischemic stroke. Depending on the extracellular pH, they exist in either one of three functional states: closed (resting), open and desensitized. While ASICs are at physiological pH 7.4 in the closed state, they open briefly upon extracellular acidification, before entering the non-conducting desensitized state. Crystal structures of the chicken ASIC1 channel in the desensitized and the open state were published several years ago. This structural information allowed, together with observations from functional studies, an understanding of the transitions between the open and the desensitized state. In contrast, the absence of structural information on the closed conformation of ASICs precluded so far a molecular understanding of their activation mechanism.

The Gouaux laboratory has now published structures of the homotrimeric chicken ASIC1 obtained at high pH by X-ray crystallography (2.95 Å resolution) and by single particle cryo-electron microscopy (3.7 Å) (1). These structures show a channel with a closed pore, representing likely the closed state. The overall structural organization is the same in all ASIC 3D structures published so far: each subunit consists of a large, complex ectodomain, two transmembrane domains, and short N- and C-termini (whose structure has not been resolved yet). The channel is formed by three identical subunits that are arranged around the central ion pore. A vestibule containing many acidic residues, the “acidic pocket”, is located on the outward-facing side of the ectodomain of each subunit, at 40-50 Å from the membrane. The main difference in the ectodomain between the closed ASIC structures and previously published open and desensitized structures is a wide opening of the acidic pocket in the structure of the closed channel.

Based on the comparison of closed, open and desensitized structures, the authors suggest the following activation mechanism: At physiological pH 7.4 the channel pore is closed and the acidic pocket has adapted an extended conformation. Extracellular acidification protonates acidic residues of the acidic pocket, thereby reducing repulsion between such residues and leading to a collapse of the acidic pocket. This movement is transmitted via central channel domains to the transmembrane helices, and leads to opening of the channel pore. A short time later, an additional movement in the central domains uncouples the ion pore from the acidic pocket and allows the transmembrane domains to relax to the non-conducting desensitized conformation. The acidic pocket will adapt its extended conformation only once the extracellular pH has returned to higher values.

This new 3D structure is undoubtedly a breakthrough in the understanding of the molecular mechanisms of ASIC activity. Some open questions remain however:

Several studies have shown that protonation events in domains other than the acidic pocket contribute to activation and desensitization, and it has also been shown that a channel in which most of the acidic residues in the acidic pocket have been neutralized can still be opened by extracellular acidification. These studies suggest that an important part of the drive for the conformational changes comes from protonation events outside the acidic pocket. This is different from the activation mechanism proposed by Yoder and colleagues, which relies on protonation events in the acidic pocket.

The cytoplasmic N- and C-termini of ASIC subunits contain sites important for ASIC function and ion selectivity. So far there is no structural information on these intracellular parts available. Future cryo-electron microscopy approaches will hopefully have the power to resolve the conformation of these domains.

Comments by Stephan Kellenberger, Université de Lausanne, Switzerland

1. Yoder, N., Yoshioka, C., and Gouaux, E. (2018) Gating mechanisms of acid-sensing ion channels. Nature, 555: 397-401. doi: 10.1038/nature25782. [PMID:29513651]

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Posted in Hot Topics

Hot topic: Engineered mini G proteins provide a useful tool for studying the activation of GPCRs in living cells

In order to stabilize the GPCR-G protein complex, an agonist must be bound to the receptor and the alpha subunit of the heterotrimer must be in a nucleotide-free state. Ground-breaking work by expert crystallographers made use of so-called mini G (mG) proteins to stabilize the active conformation of the adenosine A2A receptor in the presence of agonist and guanine nucleotides, but in the absence of Gβγ [1]. These engineered G proteins behave in a way that mimics the nucleotide-free state despite being bound to GDP; thus, they can be seen as conformational sensors of the active receptor state. This work paved the way for another study recently published in the Journal of Biological Chemistry led by Nevin A. Lambert that looked to build on this minimalistic approach to see if representative mG proteins from the four subclasses (Gs, Gi/o, Gq/11 and G12/13) could 1) detect active GPCRs and 2) retain coupling specificity [2]. Using bioluminescence resonance energy transfer (BRET) assays, the interaction between mGs, mGsi, mGsq or mG12 with prototypical GPCRs was quantified to examine whether these tools could reveal ligand efficacy/potency and G protein specificity. This was not only confirmed through exhaustive validation, but surprisingly uncovered secondary coupling interactions that might be of potential interest for follow-up studies. The GPCR superfamily comprises more than 800 GPCRs – most of which we know very little about. These elegant tools should prove valuable in increasing our knowledge about the lesser known GPCRs as well as allow for the discovery of G protein subtype-biased ligands and for unravelling receptor coupling complexity.

Comments by Shane C. Wright and Gunnar Schulte, Karolinska Institute

References

  1. Carpenter B, Nehme R, Warne T, Leslie AG and Tate CG. (2016) Structure of the adenosine A(2A) receptor bound to an engineered G protein. Nature, 536 (7614): 104-107. [PMID:27462812]
  2. Wan Q, Okashah N, Inoue A, Nehme R, Carpenter B, Tate CG and Lambert NA. (2018) Mini G protein probes for active G protein-coupled receptors (GPCRs) in live cells. J Biol Chem. pii: jbc.RA118.001975. doi: 10.1074/jbc.RA118.001975. [Epub ahead of print] [PMID:29523687]
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Hot Topic: Unexplored therapeutic opportunities in the human genome

Contemporary drug discovery is dominated by two related  themes. The first of these is target validation upon which the sustainability of pharmaceutical R&D (in both the commercial and academic sectors) crucially depends.  The second is the size of the pool of human proteins that are/could become tractable to being progressed towards clinical efficacy as their final validation step (otherwise known as the druggable proteome).  This usefully detailed review, by a large team of authors, touches on both themes but with a focus on how the community might increase the target pool by data-driven knowledge expansion for hitherto less well characterised proteins [1].

As explained in the paper, this shortfall is being addressed by the NIH Illuminating the Druggable Genome (IDG) project since 2014 [2].  As essential reading for those engaging with the  intersects between pharmacology and drug discovery, just a few aspects can be picked out. One of these is their formalisation of a target development level (TDL) classification scheme of Tclin (clinical evidence), Tchem (chemical modulators), Tbio (biological data)  and Tdark related to the depth of investigation.  This “dark” category encompasses proteins with the least current knowledge (i.e. unvalidated potential targets) and a low number of (if  any) molecular probes.  Included in this are of course the orphan GPCRs that have been the subject of previous Hot Topics in their own right [3].

The authors not only point to many additional resources but also present a wealth of detailed statistics on many aspects of drug targets.  These included (Table 1) that eight olfactory receptors have Tbio level data.  Another nugget was the fact that phenomenological responses following radiation therapy is a bona fide biological functional characterisation approach that few of us are aware of. Last but not least, we were pleased to see GtoPdb [4] cited as one of the sources included in this impressive analysis.

For the record, our own curatorially-supported human druggable target list encompasses 1496 proteins with quantitative ligand interactions.  This can be found via the UniProt cross-reference. (n.b. this number will change slightly as the links from our own latest database release will update in the forthcoming UniProt release).

Comments by Chris Southan, IUPHAR/BPS Guide to PHARMACOLOGY, @cdsouthan
References
  1. Oprea TI et al. (2018). Unexplored therapeutic opportunities in the human genome. Nat Rev Drug Discov. doi: 10.1038/nrd.2018.14 [Epub ahead of print] [PMID:29472638]
  2. Illuminating the Druggable Genome (IDG) Program. https://commonfund.nih.gov/idg
  3. Hot topic: The G Protein-Coupled Receptors deorphanization landscape.  https://blog.guidetopharmacology.org/2018/02/28/hot-topic-the-g-protein-coupled-receptors-deorphanization-landscape/
  4. Southan C et al. (2016) The IUPHAR/BPS Guide to PHARMACOLOGY in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands.  Nucleic Acids Res. 44(D1):D1054-68. doi: 10.1093/nar/gkv1037. [PMID:26464438]

 

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GtoImmuPdb: technical update March 2018 – beta-release v3

We are pleased to announce the third, beta-release of the Wellcome Trust-funded IUPHAR Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb). Since our last release in August 2017 we have implemented developments that include disease summary pages, graphical browsing features and extensions and improvements to the advanced search. This blog-post details the major developments in the v3.0 release. This release coincides with the latest 2018.1 GtoPdb release.

Portal layout (www.guidetoimmunopharmacology.org)

Some minor adjustments have been made to the portal with the social media feed panel switching to the right-hand column, updated news items included and changes to support navigation to the new disease page from the disease panel and from a new ‘Diseases’ menu bar item.

portal

GtoImmuPdb beta v3.0 portal.

Disease associations and display

A major new development has been changes to the way disease associations are presented. Previously, we had listed diseases associated to targets and diseases associated to ligands separately. It made sense to consolidate these into a single list of diseases and then to provide specific disease summary pages where all curated information about a disease could be presented. This work was done in conjunction with the Guide to PHARMACOLOGY (GtoPdb) development, as GtoPdb already contains information on target pathophysiology and mutations relating to specific diseases.

diseaselist_immuno

New disease list page. Show alphabetical list of disease, with synonyms and count of associate targets and ligands.

The new disease list page, accessed from the new menu-bar item, lists all diseases with curated data in GtoPdb/GtoImmuPdb. A convenient alphabetical list of diseases, with links to the disease summary pages, synonyms and counts of associated targets and ligands.  Our longer-term aim is to provide several disease categories, but currently only two (selected from a tab at the top) can be viewed; all diseases and immuno disease. The immuno diseases category are diseases that have data curated specifically as part of GtoImmuPdb. These are diseases that are relevant to immunology, and/or are associated to targets and ligands of immunological-relevance.

The disease summery pages have been designed to display all pathophysiology, mutation and immunopharmacology data curated in GtoPdb and GtoImmuPdb in one place. See the disease summary for Psoriasis.

General information about the disease is shown, including synonyms, descriptions, links to external disease resources (OMIM, Orphanet, Disease Ontology) and counts of the total associated targets and ligands, alongside whether there is data of immuno-relevance.

disease_summary_top

Disease summary page for Psoriasis. Top section give overview of disease, including description, synonyms and links. Counts of associated targets and ligands are shown, along with whether the disease is immune relevant.

The detailed information on each target gives a summary of any curated pathophysiology data, including the role of the target along with information on drugs and their therapeutic use and side effects. If any mutation data is available this is indicated, with links back to the relevant section of the targets detail view page. The target information also shows any specific immunopharmacology comments and ligands for which their is interaction data where the ligand is also associated with the disease.

disease_summary_target_ligands

Detailed target and ligand sections of the disease summary pages (here showing for Psoriasis).

The ligand section is currently populated with data only curated through he GtoImmuPdb project. Included is information on whether the ligand is an approved drug, immunopharmacology comments and clinical use information.

Graphical browsing (Cell types)

GtoImmuPdb has been exploring different ways for users to explore and browse data, one of which is via the use of graphics and images. We took an tree diagram of immune system cell types from Wikimedia Commons and adapted it to show the cell types for which we have data. The image was re-labelled and an image map produced to make it interactive and a way to browse to different data types.

celltype_diagram

New graphical browsing of cell types implemented in GtoImmuPdb (http://www.guidetoimmunopharmacology.org/GRAC/CelltypesForward)

Advanced Search

The search facility has been extended to cover disease, processes and cell types. This has included ensuring that search on Cell and Gene Ontology terms work by inference. For example a search on ‘cytokine’ will match a GO parent term that contains the word ‘cytokine’ and bring back targets annotated to that term, or any of it’s children.

All immunopharmacology fields (comments, top-level categories, ontology terms, ontology IDs) have now been added to the advanced search for both targets and ligands – so searches can be restricted to these fields.

adv_search

New immuno feature incorporated into the advanced search

Process Associations – GO evidence display

We have adjusted the display of GO terms in both Process Association to Target pages and the target detailed view pages. On the target detailed view page, the section on process associations only show GO term associated to the target if the have GO evidence other than ‘IEA’  (inferred by electronic annotation).  The IEA evidence is the only evidence used by GO that “is assigned by automated methods, without curatorial judgement”. As such we hide these by default (but users can expand the section to see them). On the process association page, the IEA terms are show, but italicised, to emphasise this difference.

proces_assoc_iea

Modifications to show/hide GO associations with IEA evidence.

Help

To reflect the changes made in this release our help pages have been updated (http://www.guidetoimmunopharmacology.org/immuno/immunoHelpPage.jsp), and we intended to follow this up by putting in place in-line pop-up help, help videos and a revised tutorial.

This project is supported by a 3-year grant awarded to Professor Jamie Davies at the University of Edinburgh by the Wellcome Trust (WT).

Posted in Guide to Immunopharmacology, Technical

Database release 2018.1

Pharmacology Search results table
The first GtoPdb and GtoImmuPdb beta release of  2018 includes plenty of target and ligand updates as well as announcing some important new features.
As always, full content statistics for release 2018.1 can be found on the database about page.

New website features

Disease listing and disease pages

For the first time, disease information has been gathered together in one place, under a new menu bar option called “Diseases”, which links to a full listing of all the diseases described in GtoPdb. In addition, an “Immuno disease” tab links to a listing of diseases that are relevant to immunology and linked to targets and ligands in GtoImmuPdb.

The table includes the number of targets and ligands that have been associated with the disease by our curators (note, so far only the relationships between ligands relevant to immunological diseases have been formalised in the database structure, so many diseases are not yet linked up to relevant ligands/drugs).
Individual disease pages include information about the disease, such as synonyms and links to Disease Ontology, OMIM or Orphanet where available.
Targets and ligands linked to the disease are listed, with information on disease-causing mutations if known. As noted above, currently the only ligands that have been formally associated with diseases cover the immunopharmacology domain, but we hope to extend this in the future. For further details see the help documentation.
The GtoPdb disease listing

The image shows part of the full disease list. The immunologically-relevant diseases are also shown under a dedicated tab.

Disease list and disease summary pages

Showing a disease summary page with links to external resources and listing the associated targets and ligands in GtoPdb/GtoImmuPdb.

Pharmacology search tool

The new Pharmacology search tool and browser can be found under the Advanced search drop-down menu. This tool allows users to upload target ID sets to retrieve a list of ligands which modulate those targets. Detailed information on how to use it can be found in the help page. After uploading a list of IDs (e.g. UniProtKB accessions or Ensembl gene IDs), select the number of interactions to show, and optionally, the species for the target of the interaction. By default, the results will show the top 5 interactions ordered by decreasing affinity. On the results page, the targets are ordered by how many interactions they have that match the search criteria, with 10 targets per page. A more detailed table of results (including ligand structures and affinity values) is available to download as a CSV file by clicking the “Download” button at the top of the page.
Pharmacology Search results table

Showing a section of the results page following a Pharmacology Search. The default search returns the top 5 interactions for each target.

We’ll be extending the functionality of the tool over the next few months, so please send us your feedback and bug reports to the usual email address!

Target updates

These are some of the targets which have been updated in the new release.

GPCRs

GPR35 (Class A Orphans)
ACKR3 (Chemokine receptors)

Ion channels

Transporters

ATP-binding cassette transporter family
SLC22 family of organic cation and anion transporters

Enzymes

An update has brought our BACE1 lead inhibitors collection up to 20 with the addition of elenbecestat (E2609) and RO5508887 as clinical candidates, NB-360 with a good brain penetration and Compound 12 [PMID:28626832] as an interesting precedent of a fragment with a PDB structure.  Some of these also have approximate equipotency against with BACE2. Since nearly all BACE1 inhibitors have failed clinically over the last decade (with the Merck verubecestat even having abandoned the prodromal arm) the prospects for this mechanism of action look so bleak as to challenge the central hypothesis of APP secretase target validation.  Our entries now give research groups the option of direct mouse model translational comparisons between these leads in the hope of providing at least some insight into failures and possible progress.

Other new data

From time to time we select entries from relatively new journals that are including quality pharmacology papers.  This release includes two examples. The first of these, the BACE1-binding fragment in PDB, is from ACS-Omega.  The second, a new GtoImmuPdb S1P1 inhibitor entry, is from Pharmacology Research & Perspectives as the new Wiley/ASPET journal.

Two members associated with GtoPdb recently presented at the SAFER project kick-off meeting.  The aim is to provide mechanistic insights and pharmacological tools towards safer treatments for neurological diseases focusing initially on 5-HT2A and the training of PhD students.  As a proof of concept for capturing new relevant structures, we have now added a sub-nanomolar 5-HT2A inhibitor to the database.

New data in the Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb)

Since the last release at least 32 targets and 66 ligands have been added to GtoImmuPdb. The 2018.1 release also coincides with the beta 3 release of the GtoImmuPdb portal – more details of which are available in a separate blog post. Other highlights include +20 ligands associated to immunological diseases, +1 target associated to disease, +57 targets associated to processes, and +8 targets associated to cell types.
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Posted in Database updates, Technical

Hot topic: The G Protein-Coupled Receptors deorphanization landscape.

Within the vast GPCR superfamily, orphans are described as receptors devoid of known endogenous ligands. They have been labeled as 7 transmembrane proteins by sequence homology and dispatched accordingly in the different GPCR subfamilies. They have attracted much attention given the recognized potential of GPCRs in terms of drug discovery. It is anticipated that discovering a new (and in the best case: previously unknown) ligand for an elusive receptor will open avenues in terms of innovative physiological concepts as well as unprecedented opportunities for drug discovery. However, after a couple of striking deorphanizations that confirmed their potential, the number of successful pairings between ligands and receptors has decreased.

The present paper by Laschet, Dupuis & Hanson [1] sheds some light on the current state of the field and the phenomenon of reduced discoveries in the orphan landscape. Although it is true that fewer deorphanizations have been reported recently compared to the 1990-2000 period, the authors propose that the rate has reached a “steady-state” stage. Nevertheless, with more than 100 remaining orphans, the daunting task of full deorphanization that lies ahead will require creative approaches both at the technical and conceptual level. Thus, following short historical reminders, the authors provide an extensive description of the current methods applied to deorphanization as well as emerging techniques that should help pharmacologists active in the orphan GPCR field in the near future. In addition, this review lists and discusses the deorphanizations that appeared in the literature since the last comprehensive state of the art issued by the IUPHAR (in 2013) [2] and put these pairings in their contexts, describing the probable outcomes in terms of new drug targets and previously unforeseen physiological loops.

Finally, during the collection of the recent literature about orphans, the authors noticed an important number of unconfirmed pairings and identified this as one of the major issues of the field and an important challenge for the future. Beside the deorphanized receptors that became silent after a single publication, presumably because of the failure of confirmation attempts by other teams, some ligands were openly questioned by recently published negative datasets. The paper proposes tentative explanations for inconsistencies in the literature and suggests recommendations such as critical controls that should be included when reporting a ligand for an orphan receptor.

Comments by Julien Hanson, University of Liege

  1. Laschet C, Dupuis N, Hanson J. (2018) The G Protein-Coupled Receptors deorphanization landscape. Biochem Pharmacol. pii: S0006-2952(18)30073-X. doi: 10.1016/j.bcp.2018.02.016. [Epub ahead of print] [PMID:29454621]
  2. Davenport AP, et al. (2013) International Union of Basic and Clinical Pharmacology. LXXXVIII. G Protein-Coupled Receptor List: Recommendations for New Pairings with Cognate Ligands. Pharmacol Rev. 65: 967-86. [PMID:23686350]

Note, the GtoPdb latest pairings page tracks reports of novel pairings between orphan receptors and their ligands.

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Posted in Hot Topics

Hot topic: Pharmacogenomics of GPCR Drug Targets

A system of rigorous clinical trials and regulation exist to ensure that a new drug is safe and effective when reaching the market. However, natural human genetic variation(s) may cause individuals to respond differently to the same medication. A collaboration between the MRC Laboratory of Molecular Biology, Cambridge (UK), the Scripps Research Institute in Florida and the Department of Drug Design and Pharmacology, University of Copenhagen (home of the GPCRdb team) has now published a new detailed study on the effects of genetic variation in G protein-coupled receptors on responses to FDA-approved drugs [1].

The authors address the following main questions:

  • How variable are GPCR drug targets in the human population?
  • Are individuals with variant receptors likely to respond differently to drugs?
  • What is the estimated economic burden associated with variation in GPCR drug targets?

To address these questions, the authors have analysed datasets from multiple sources including genotype information from the 1,000 Genomes project, exome sequencing data from the exome aggregation consortium (ExAC), which contains aggregated information on genetic variants for ~60,000 ‘healthy’ individuals, structural information of receptors in complex with diverse ligands, data on functional effect of mutants and information on drug sales from the UK National Health Service.

The study reports that on average, an individual carries 68 missense variations in approximately one-third of the 108 GPCR drug targets. Many FDA approved drugs target a number of highly variable GPCRs. For example, several genetic variants for the mu-opioid receptor selected for experimental characterisation show an altered response for FDA-approved drugs, which could potentially lead to no or adverse reactions in the human population. Several variants occur within drug-binding sites and other functionally important positions, such as for the CCR5 drug-binding pocket of maraviroc, an antiretroviral drug for HIV treatment.

Based on an economic model, the authors estimated the potential economic burden due to ineffective prescribing of GPCR targeting drugs to be between 14 million and half-a-billion pounds annually in the UK alone.

This work might inspire many scientists to characterise human variants from multiple angles similar to the ENCODE project.

Key highlights:

  • GPCRs targeted by FDA-approved drugs show genetic variation in the human population
  • Genetic variation occurs in functional sites and may result in altered drug response
  • We present an online resource of GPCR genetic variants for pharmacogenomics research
  • Understanding variation in drug targets may help alleviate economic healthcare burden

(1) Hauser AS et al. (2017). Pharmacogenomics of GPCR Drug Targets. Cell, 172(1-2):41-54.e19. doi:10.1016/j.cell.2017.11.033. [PMID:29249361]

Comments by Alexander Hauser, University of Copenhagen and GPCRdb

While the above is a tour de force for GPCRs note also the genetic variation from 1K Genomes and/or ExAC can be accessed for every target protein in GtoPdb via the Ensembl gene ID we cross-reference.  

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Posted in Drug targets, Hot Topics

PubMed Commons and Altmetrics

This has been split from an updated older post on Citation profiles for our NAR and Concise Guide papers  and this section will be updated soon

PubMed Commons
In addition to keeping an eye on citations per se we also folow up on some of the newer ways of increasing the findability and connectivity of our work in the ever more complex bibleometrics/Social Media ecosystem.  These efforts are modest (compared to what can be done) since we have our heads down for the Day Job but some of them have become necessary  house-keeping . These include grant linking,  the addion of  ORCHIDs  for team members (both of these as  EPMC functionality) and making sure papers are entered into our very own Edinburgh Research Explorer (actually highly ranked in Google for title searches).

Two other aspects may be of  interest (they can’t be detailed here but background is in the links). The first of these is the use of PubMed Commons. that has several utilities for us, including being able to “daisy chain” forward citaion pointers (but you wont see them in EPMC yet).  For example, amoung the 73 PubMed  citations for our 2009 NAR paper, 7 are 2015 and 2 from 2016. Thus, some recent authors are still citing our oldest paper (we see this across the series in fact  but, to be fair, some of them could be giving us the courtesy of multiple NAR cites although I have not checked). We therefore came up with the strategy of adding discrete pointers in PubMed Commons. As it happened, the last one (pictured below) was added most recently, even thought it is first in the chain by abstract date.

commons-pointer

So, if  the scholars in question happen to check PubMed (n.b. but not  BJP authors, since the most recent NAR reference would have been added by the Editors anyway) we have now have a set of  comments to point the four older papers forward to the fifth 2016 paper (and should we be fortunate enough to get accepted for a future NAR Database issue, we would then add a new comment to the chain).  Consequent to the posting above, an unexpectedly prominent  ping appeared  below, on the 2nd of Feb, highlighted in yellow.

pubmed_commons_comment_feb_2017

In a nutshell, “Featured comments” just happend to automatically select ours (but it seems like an actual human edited it)  which consequently featured on the PubMed front page, no less, giving us 24 hours of micro-fame!  As icing on the cake, the concomitant dailly auto-tweet of the heuristic chart-toppers, shown below, reached 4394 followers of the PMCom account (and was re-tweeted by us of course)

pubmed_commons_tweet_feb_2017

Altmetrics
Continuing on the metrics theme, in the panel below you can see Altmetrics scores for our same five NAR papers, plus the one Kudos entry.

altmetrics_nars

These outlinks can be found under the right-most “External links” tab on any EPMC entry that has them. The Altmetrics Rosette and sub-scores give a general measure of interest asssociated with a paper (but dont forget this may not necessarily be completely positive)  broken down by category, as you can see for our 2016 NAR below;

altmetric

Interesting aspects of Almetic scores include that they are faily immediate (i.e. accumulating within the first month or so)  and tend to move in the oposite direction to the slower accumulation of cites (i.e.they flatten off).  Here again, we alow ourselves a little warmth of feeling to see that the Altmetrics hueristics (while not incontravertable)  puts us close to the top-10% of comparable publications for both our GtoPdb NARs (i.e. we got the word out). The older papers, published during LBA (Life Before Altmetrics), clearly pick up lower scores. To conclude by putting it on the  record, we are most appreciative of colleagues and compatriots who explicitly draw positive attention to our work in both traditional and altenative ways.

Posted in Uncategorized

Hot topic: Trends in GPCR drug discovery: new agents, targets and indications

New avenues for GPCR drug discovery have emerged owing to recent advances in receptor pharmacology, technological breakthroughs in structural biology and innovations in biotechnology. A collaboration between the Department of Drug Design and Pharmacology, University of Copenhagen (home of the GPCRdb team) and the Uppsala University have published a detailed analysis of all GPCR drugs and agents in clinical trials, which reveals current trends across molecule types, drug targets and therapeutic indications [1].

By manually curating CenterWatch’s Drugs in Clinical Trials database and cross-referencing with public sources (such as Drugbank, Pharos and Open Targets), they were able to identify 475 approved drugs that target 108 unique GPCRs (~34% of all FDA-approved drugs) (http://www.gpcrdb.org/drugs/drugmapping). Additionally, there are approximately 321 agents that are currently investigated in clinical trials, of which ~20% target 66 potentially novel GPCR targets with no approved drug yet. Of these, 37 are peptide or protein-activated GPCRs.

Other relevant highlights:

  • Based on this data, the authors calculated GPCR-targeted agent success rates of 78%, 39% and 29% for phases I, II and III, respectively — slightly higher than the FDA’s average for all investigated agents.
  • There are early indications that the proportion of GPCR-targeted biologics such as monoclonal antibodies (mAbs) and other recombinant proteins is increasing in early stage clinical trials.
  • There is increasing focus on target selectivity rather than polypharmacology.
  • More allosteric modulators in early stage clinical trials.
  • CNS disorders remain highly represented among the indications of GPCR-targeted agents.
  • Diabetes is highly represented among the GPCR-targeted agents currently in clinical trials.
  • Opportunities are emerging for GPCR-targeted agents in oncology.
  • The GPCR structures are starting to impact drug discovery.

Currently, established GPCR drug targets are used by an average of 10.3 (median = 4) distinct approved agents. This indicates a near saturation of the current target space, and emphasizes the need to identify new druggable receptors in order to develop novel medications. The 224 (56%) non-olfactory GPCRs that are yet to be explored in clinical trials have broad untapped therapeutic potential, particularly in genetic and immune system disorders.

Comments by Alexander Hauser and David Gloriam, University of Copenhagen and GPCRdb.

[1] Hauser AS, Attwood MM, Rask-Andersen M, Schiöth HB, Gloriam DE. (2017) Trends in GPCR drug discovery: new agents, targets and indications. Nat Rev Drug Discov. 16(12):829-842. doi: 10.1038/nrd.2017.178. [PMID:29075003]

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Posted in Hot Topics

Impact statements and content subsumation: BPS 2017 follow-up

We were pleased to catch up with many GtoPdb/GtoImmuPdb users, aficionados, friends and affiliates at the BPS Pharmacology 2017  in the QEII Center in London.  You can find our presentations and posters on Slideshare.  Associated with this presence we have an important request to ask of users and downloaders, plus a related request for the latter.  These are being made in the context of future funding considerations in general and a pending application to become an ELIXIR Europe Core Resource  in particular (we joined the UK ELIXIR Node Resources last year).

We need to collect and collate  “impact statements” (a.k.a. “use cases” or “translational stories”).  For this we would be most grateful to receive comments from users, regardless of whether new or experienced, academic or commercial.   We are pleased to have received many general compliments by different routes in recent years (including via our enquiries e-mail and Twitter) but we would like these new statements to give concrete and specific examples of the utility of our resource (detail is good but does not have to be long).   This can not only include answering scientific competency questions but also educational impact (e.g. as curricular inclusions for pharmacology teaching). We will contact some of you who we engaged with at BPS 2017 (where the level of positive response was gratifyingly high)  but please just e-mail us at our usual address: enquiries at guidetopharmacology.org

The second request is for those who either point to us as outlinks and/or subsume our content via downloads  or webservices. These may be either as part of integration efforts or simply bringing it inside their firewalls.  When we looked at in-links (i.e. resources pointing to us) last year were surprised to find well over 20 of these, about half of which we were unaware of.  From citations of our 2016 NAR Database Issue paper (PMID: 26464438) we have found several new ones but we think there may be more we have either not picked up and/or who have not contacted us.  Clearly, since having our content pointed to and/or subsumed is direct evidence of impact, we would be happy to have short testimonies to this effect, in particular why we were selected (n.b. commercial enterprises need not detail their internal why’s and wherefores but even general comments in this context are still useful).  If any parties could send both types of  examples (direct usage and subsumation) so much the better.

Note also that we welcome technical contact with all resources subsuming our content. This is not only to see if we can enhance the ease of this as a process but also to assist with making sure the latest releases are picked up. This is important since these have now reached six per year (a schedule we hope to maintain in 2018).  We are aware of some meta-portals whose internal update cycles exceed this so we want to avoid them missing out on our most recent data.

Clearly we need any comments you send us to be provenanced with personal professional identities and organisational affiliations. Notwithstanding, for those applications we are currently considering nothing will be publically surfaced.  Anyone who would like do us the favour of  presenting their use case but needs anonymity, is still welcome to contact us (n.b. enquiry mails are only seen by core team members)

 

Posted in Uncategorized

Database release 2017.6

The sixth and final IUPHAR/BPS Guide to PHARMACOLOGY release of 2017 has been published on 29th November. This release includes new content for the Guide to IMMUNOPHARMACOLOGY, which is currently still in beta phase. This release includes the following updates and new features:

Targets

Several new immunology-relevant proteins, across several target classes, have been added, along with ligands that interact with them.

target symbol TID target class GtoImmuPdb
VSIR

2956

Other protein y
BCL6

2957

Other protein y
FOXN1

2958

Other protein y
GPC3

2959

Other protein y
TRIM21

2967

Enzymes y
IL-1R8

2969

Catalytic Receptors y
EPHX2

2970

Enzymes y

Further new ligands have also been added for existing targets.

The following existing targets have been reviewed and updated:

GPCRs:

The GPCR overview text has been updated with information on pseudogenes and olfactory receptors.

Ion channels:

New website features

The ability to download the results of database searches has been added. Click on the “Download” button at the top of the search results page to download a CSV file listing some basic information on the targets, ligands and families in the results. The file includes GtoPdb identifiers, UniProt accessions, gene symbols and ids, and ligand chemical structure identifiers. We intend to develop this further, possibly with customisable download options, and we welcome feedback on this feature to inform future development.

Image showing the new Download button

New Download as CSV option for search results

The Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb) has issued the beta v2.2 release (see more details in the November technical blog) which includes an extension to the target advanced search. This now enables searching across the main GtoImmuPdb data types (processes, cell type and disease). Built into this is inferred searching of Gene Ontology and Cell Ontology terms. By way of example, if a user searches on the term ‘cytokine’ this will match to any GO term containing that term. The search results will then bring back any targets annotated to that term or any of its children. The results will display the matched parent terms, plus a count of the number of child terms annotated to the target (see screenshot below).

cytokine_result

The above screenshot shows the first results for a search on ‘cytokine’. The target TLR4 is returned as it is annotated to many GO terms, or their children, where the GO term contains the word ‘cytokine’. For example, TLR4 is annotated to 24 terms that are children of the term ‘regulation of cytokine production’.

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Posted in Database updates, Guide to Immunopharmacology, Technical

GtoPdb at Pharmacology 2017

The GtoPdb team will be at the British Pharmacological Society’s flagship meeting, Pharmacology 2017, in London, December 11-13th 2017.

We are pleased to have our own stand at this meeting and will be present during the refreshment breaks and poster sessions, where we look forward to speaking with database users and give live demos of the website. We will also be helping out at the Wiley stand in the Wiley Networking Lounge to publicise the Concise Guide to PHARMACOLOGY 2017/18, so look out for the events happening there and come and collect your free CGTP USB wristband!

In addition, GtoPdb team members will be presenting during the following slots in the main programme on Wednesday 13th Dec:

Oral Presentations

Abstract Number: OE004
Abstract Title: The IUPHAR/BPS Guide to PHARMACOLOGY in 2017: new features and updates
Date: Wednesday, December 13, 2017, 11:30 AM
Oral Session: Oral Communications: Education

Abstract Number: OB073
Abstract Title: Capturing new BIA 10-2474 molecular data in the IUPHAR/BPS Guide to PHARMACOLOGY
Date: Wednesday, December 13, 2017, 11:30 AM
Oral Session: Oral Communications: Mixed Tracks

Lunchtime Flash Poster Presentations

Flash Poster Number: FP35
Poster Number: PB128
Abstract Title: Iuphar guide to Immunopharmacology
Date: Wednesday 13 December 2017
Presentation Time: 1:15 PM – 1:45 PM

Flash Poster Number: FP33
Poster Number: PE005
Abstract Title: Navigating links between structures and papers: PubMed-to-PubChem connectivity from the Guide to PHARMACOLOGY and the British Journal of Pharmacology
Date: Wednesday 13 December 2017
Presentation Time: 1:15 PM – 1:45 PM

Poster Presentations

Abstract Number: PB128
Abstract Title: Iuphar guide to Immunopharmacology
Date: Wednesday, December 13, 2017, 2:45 PM
Poster Session: Poster Session: Integrated Systems Pharmacology

Abstract Number: PB135
Abstract Title: A systems pharmacology study of the cholesterol biosynthesis pathway
Date: Wednesday, December 13, 2017, 2:45 PM
Poster Session: Poster Session: Integrated Systems Pharmacology

Abstract Number: PE004
Abstract Title: The international Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification (NC-IUPHAR): Relevance to pharmacology today and challenges for the future
Date: Wednesday, December 13, 2017, 2:45 PM
Poster Session: Poster Session: Education and Skills

Abstract Number: PE005
Abstract Title: Navigating links between structures and papers: PubMed-to-PubChem connectivity from the Guide to PHARMACOLOGY and the British Journal of Pharmacology
Date: Wednesday, December 13, 2017, 2:45 PM
Poster Session: Poster Session: Education and Skills

Abstract Number: PE011
Abstract Title: The IUPHAR/BPS Guide to PHARMACOLOGY in 2017: new features and updates
Date: Wednesday, December 13, 2017, 2:45 PM
Poster Session: Poster Session: Education & Skills

We look forward to seeing you there!

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Posted in Concise Guide to Pharmacology, Events

GtoImmuPdb: technical update November 2017

This blog-post will discuss the major developments planned for the Guide to IMMUNOPHARMACOLOGY as we look ahead to our next beta-release (v3.0) in early 2018.

This month, the updated IUPHAR/BPS Guide to PHARMACOLOGY NAR Database Issue has been published online (https://academic.oup.com/nar/article/4628131). [PMID: 29149325]

The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: updates and expansion to encompass the new guide to IMMUNOPHARMACOLOGY
Nucleic Acids Research, gkx1121, https://doi.org/10.1093/nar/gkx1121

As the title indicates, a major part of this update includes the expansion of the database and developments to produce the new Guide to IMMUNOPHARMACOLOGY. The paper discusses the unique targets and ligands that have been incorporated into GtoPdb as a consequences of the GtoImmuPdb Project. For example targets of relevance to immunity, inflammation and infection such as pattern recognition receptors and protein of the innate immune response. Database content statistics are presented with a specific breakdown for GtoImmuPdb content (Table 1).

nar2018_table1

Table 1. Taken from the NAR paper, table gives a breakdown of database content statistics, including GtoImmuPdb counts.

The paper goes into details on the development of the Guide to IMMUNOPHARMACOLOGY in terms of content & curation and how targets and ligands of immunological relevance are identified. There is detailed discussion on the process of incorporating the new process, cell type and disease data types for GtoImmuPdb as well as explanations of the novel portal and interfaces that have been developed to surface the GtoImmuPdb data.

The discussion and descriptions in the paper are related to the beta-release v2.0. Our next planned beta-release is due in early 2018. The developmental priorities for this release are;

  • Improving disease associations and display
  • Graphical browsing / navigation
  • Advanced search tool for immuno data types
  • Video help tutorials

For the disease data we are looking at developing new disease summary pages. These will not only serve to display target and ligand associations to disease of immunological relevance – but will also capture and display all disease-related data in the GtoPdb. This includes pathophysiology data and information on mutations. We are currently working-up some prototype pages, but expect to be able to have have some form of disease pages available in beta v3.0.

Using graphical illustrations of key biological pathways and cell types, as a way to summarise data can be very valuable. Enabling such graphics to be interactive and support navigation of a website may bring added value to the GtoImmuPdb resource. We are at the early stages of developing a cell types graphical-based navigation tool (Figure 2).

pathophysiologyAutoImmunity_text800

Figure 2. Graphical illustration of key immunological cell types. This forms the basis of providing a graphical-based navigation tool for GtoImmuPdb. Image copyrighted

Until now we haven’t developed the existing advanced search to cover GtoImmuPdb data types – this will be addressed in beta v3.0. We are also planning to provide video help tutorials to guide users in navigating the main GtoImmuPdb data types.

This project is supported by a 3-year grant awarded to Professor Jamie Davies at the University of Edinburgh by the Wellcome Trust (WT).

Posted in Guide to Immunopharmacology, Technical

Hot topic: Cryo-EM structures of Mucolipin TRP Channels in the Lysosome: Five Together at Once

The mucolipin subfamily of Transient Receptor Potential (TRP) channels, which consist of TRPML1, TRPML2, and TRPML3 (a.k.a. MCOLN1- 3), are Ca2+-permeable cation channels localized in intracellular endosomes and lysosomes. In response to cellular stimulation, TRPMLs mediate Ca2+ release from the lysosome lumen, triggering Ca2+-dependent lysosomal membrane trafficking events involved in a variety of basic cell biological processes, including lysosomal exocytosis, autophagy, and membrane repair [1]. In humans, loss-of-function mutations of TRPML1 cause type IV Mucolipidosis (ML-IV), a lysosome storage neurodegenerative disease (LSD). In mice, gain-of-function mutations of TRPML3 cause pigmentation and hearing defects [1]. Phosphatidylinositol 3,5-bisphosphate (PI(3,5)P2), an endolysosome-specific phosphoinositide, may serve as an endogenous agonist of TRPMLs [2]. In addition, mucolipin-specific synthetic agonists (ML-SAs) have been identified and shown to regulate various TRPML-dependent lysosome functions by mimicking endogenous agonists [3]. Now, five independent studies, led by Youxing Jiang, Xiaochun Li, Soek-yong Lee, Maojun Yang, and Jian Yang, respectively, report a total of three TRPML1 and two TRPML3 Cryo-EM structures, all at atomic resolution, and in both closed and agonist-bound open conformations [4-8]. The general features of these channels are consistent across all five studies. Consistent with previous work [2], positively-charged amino acid residues in the cytoplasmic N–terminus are found to be responsible for channel activation by PI(3,5)P2 [7, 8]. In contrast, the synthetic agonist ML-SA1 binds to a separate site at an intriguing location. TRPML1 and TRPML3 are six-transmembrane (6TM) channel proteins with an overall topology similar to many other tetrameric cation channels, including KV channels. ML-SA1 binds to residues in the S5 and S6 [4, 6], domains that are known to form the “activation gate”. These five studies have provided a structural foundation for studying TRPML channel regulation, pharmacology, and lysosome chemical biology, which in turn may help develop new therapeutic strategies for a spectrum of lysosome-related diseases, including ML-IV, other LSDs, and common neurodegenerative diseases.

Comments by Haoxing Xu, NC-IUPHAR subcommittee Chair of the Transient Receptor Potential Channels and Professor, the University of Michigan

References

1. Xu, H. and D. Ren, Lysosomal physiology. Annu Rev Physiol, 2015. 77: p. 57-80. [PMID:25668017]

2. Dong, X.P., et al., PI(3,5)P(2) Controls Membrane Traffic by Direct Activation of Mucolipin Ca Release Channels in the Endolysosome. Nat Commun, 2010. 1(4). [PMID:20802798]

3. Shen, D., et al., Lipid storage disorders block lysosomal trafficking by inhibiting a TRP channel and lysosomal calcium release. Nat Commun, 2012. 3: p. 731. [PMID:22415822]

4. Zhou, X., et al., Cryo-EM structures of the human endolysosomal TRPML3 channel in three distinct states. Nat Struct Mol Biol, 2017. [PMID:29106414]

5. Zhang, S., et al., Cryo-EM structures of the mammalian endo-lysosomal TRPML1 channel elucidate the combined regulation mechanism. Protein Cell, 2017. 8(11): p. 834-847. [PMID:28936784]

6. Schmiege, P., et al., Human TRPML1 channel structures in open and closed conformations. Nature, 2017. 550(7676): p. 366-370. [PMID:29019983]

7. Hirschi, M., et al., Cryo-electron microscopy structure of the lysosomal calcium-permeable channel TRPML3. Nature, 2017. 550(7676): p. 411-414. [PMID:29019979]

8. Chen, Q., et al., Structure of mammalian endolysosomal TRPML1 channel in nanodiscs. Nature, 2017. 550(7676): p. 415-418. [PMID:29019981]

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Posted in Hot Topics

The Concise Guide to PHARMACOLOGY 2017/18

310612-BJP-ConciseGuide-300x150px

Concise Guide to Pharmacology Simplifies Drug Discovery Research

The Concise Guide to PHARMACOLOGY 2017/18 (CGTP), which is produced from a subset of the data contained in the IUPHAR/BPS Guide to PHARMACOLOGY database, is now available in the British Journal of Pharmacology. Published by Wiley on behalf of the British Pharmacological Society, the 440 page guide includes overviews of key properties for close to 1,700 human drug targets, identifies 3,500 ligands including more than 2,400 synthetic organic molecules and over 50 antibodies. Over 4,000 interactions between ligands and targets are quantified, allowing researchers to assess the potency of these interactions.

This open access knowledgebase of major drug targets is completely linked and divided into eight major areas of research focus:

  • G protein-coupled receptors
  • Ligand-gated ion channels
  • Voltage-gated ion channels
  • Other ion channels
  • Nuclear hormone receptors
  • Catalytic receptors
  • Enzymes
  • Transporters

It also includes an Overview chapter with additional information on other protein targets.

“As a pharmacologist, being able to access freely information on current human drug targets is vital to discovering new therapeutics,” said Steve Alexander, Associate Professor of Molecular Pharmacology, Faculty of Medicine & Health Sciences at the University of Nottingham and Lead Editor of the Concise Guide.

The Concise Guide provides an authoritative voice on nomenclature of these pharmacological targets through close links with NC-IUPHAR. It offers summary information on the best available pharmacological tools, alongside key references and suggestions for further reading.

“The Concise Guide to PHARMACOLOGY is the drug discovery researchers’ bible,” said Amrita Ahluwalia, Co-Director, The William Harvey Research Institute, Professor of Vascular Pharmacology at Barts & The London School of Medicine & Dentistry, and Editor-in-Chief of the British Journal of Pharmacology. “We are pleased to once again make the Concise Guide freely available to our colleagues around the globe at www.guidetopharmacology.org/concise.”

This edition of the Concise Guide was compiled with the help of over 150 collaborators representing industry and academia from 22 countries across four continents. The British Pharmacological Society and the Guide to PHARMACOLOGY database team would like to thank the CGTP editors, contributors, and colleagues at the Universities of Cambridge, Edinburgh, Nottingham in the UK, and Monash, Australia for their contributions to updating the Concise Guide to PHARMACOLOGY.

The Concise Guide is a handy starting point for teaching and researching on specific pharmacological targets. All the targets and ligands are also linked directly to the online database for further details. Please share this URL widely with your students and colleagues.

Citation:

Alexander SPH, Kelly E, Marrion NV, Peters JA, Faccenda E, Harding SD, Pawson AJ, Sharman JL, Southan C, Buneman OP, Cidlowski JA, Christopoulos A, Davenport AP, Fabbro D, Spedding M, Striessnig J, Davies JA; CGTP Collaborators. (2017) The Concise Guide to PHARMACOLOGY 2017/18. Br J Pharmacol. 174 (Suppl 1): S1-S446. [PMIDs: 29055037, 29055040, 29055033, 29055038, 29055036, 29055035, 29055034, 29055039, 29055032]

Publication URL: http://bpspubs.onlinelibrary.wiley.com/hub/issue/10.1111/bph.v174.S1/

Infographic

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Posted in Concise Guide to Pharmacology, Publications

GtoPdb NAR database issue 2018: Journal to database connectivity and journal to GtoPdb links

The following blog post acts as supplementary data to the 2018 NAR Database Issue

Journal to Database connectivity

The citation provenance of all entity records and contextual comments selected by the curators and NC-IUPHAR members in GtoPdb is supported by four document types. These are journal papers with PubMed Identifiers (PMIDs, 30,894), journal papers without PMIDs (246), book references (72) and patent numbers (412). We also have 109 URL-only citations we have judged of good reputation and expected stability (some of which will get displaced when appropriate journal papers appear). The key axis of connectivity that we facilitate is PubChem-to-PubMed reciprocal linking. The importance of this overall has been described by the PubChem team in some detail, including the contribution of GtoPdb as one of the mapping sources [1].

The set of curated ligand references (for quantitative activity data at targets as well as selected ancillary references, such as completed clinical trial reports) form part of the SID records we submit to PubChem, which has a number of linking consequences. Note also that we uniquely specify the explicit location of the ligand structure within the reference. For example, ligand id: 8135 is named “compound 21 [PMID: 23312943]” and can thus be discriminated from no less than seven other “compound 21”s in the database by their specific PMID suffixes. Figure 1 illustrates the link between GtoPdb compounds and “Depositor Provided PubMed Citations” (DPPMC) both in the SID from us and merged in the CID from other submitters. Crucially, this relationship is reciprocal as we can see in the lower panel of Figure 1. This means that any user coming in to the NCBI Entrez system [2], either via PubMed or PubChem, can connect the paper to the structure or vice versa. In this example, we are the only source that has submitted a connection and the structure can be located in the paper (i.e. as compound 21). Conversely, popular compounds (e.g. approved drugs) may have PubMed connections in their CIDs from many submitters, but ours will include the quantitative binding data reference which may be before the drug was awarded an International Nonpropietary Name (INN).

Figure11

Figure 1.  GtoPdb to PubChem to PubMed connectivity for ligand 8135.

Our overall PubMed statistics are shown in Table 1.

Table 1. GtoPdb PubMed statistics

 

All PMIDs curated into GtoPdb

30,894

Associated with target annotation

22,060

Associated with ligand annotation

9,673

Ligand SIDs (from 8978) that have PMID links

7,374

Total PMID links

9,086

Associated with ligand interactions or comments in PubChem

8,756

Associated with quantitative ligand interactions in PubChem

6,011

 

The majority of PMIDs (22,060) are associated with individual targets as well as commentaries on families, accumulated from curation and committee updates over 14 years. Internally we can attribute 9,673 PMIDs to ligand-specific references. From our 8978 SIDs, 82% have at least one DPPMC making a total of 9,086 PMID links. Of these, 6,011 refer to the quantitative interaction. We have analysed the journal breakdown for our ligands as shown in Figure 2 which reflects our empirical primary, secondary and tertiary reference classifications. For example, primary citations as first reports of binding data between ligands and targets are often selected from the Journal of Medicinal Chemistry, while we generally cite the British Journal of Pharmacology (BJP) in relation to in vivo rodent pharmacology, and occasionally the British Journal of Clinical Pharmacology (BJCP) for clinical trial reports. To discern if there was an immunopharmacological curation signal in our literature we compared Figure 2 with the PMIDs only from GtoImmuPdb. It was interesting to note that for the primary references we selected for quantitative ligand interactions, the overall pattern was similar. Notably, however, Journal of Immunology had moved up from a ranking of 17th in Figure 2 to 6th in the GtoImmuPdb references.

Figure12

Figure 12.  Top-twenty journals from the 8,756 PMIDs cited in the interaction comments.

Journal-to-GtoPdb links

Our engagement with the BJP in the provision of live out-links has been described previously [3]. The major enhancement for this year is that Wiley have transitioned to in-line links in the text (at first mention), rather than the previous method of adding separate tables to the manuscripts. Taking the recent BJP papers from Volume 174, Issue 18 September 2017 as an example, the 12 papers therein have 134 out-links to GtoPdb. This year has also produced our first “circular” example where GtoPdb team members are co-authors on a Systems Pharmacology study, partly derived from the database for which we have added a set of links “back in” [4]. This year Wiley have also introduced the same GtoPdb out-links for the BJCP.

1. Kim, S., Thiessen, P.A., Cheng, T., Yu, B., Shoemaker, B.A., Wang, J., Bolton, E.E., Wang, Y. and Bryant, S.H. (2016) Literature information in PubChem: associations between PubChem records and scientific articles. J Cheminform, 8, 32. PMID: 27293485

2. Gibney, G. and Baxevanis, A.D. (2011) Searching NCBI databases using Entrez. Current protocols in bioinformatics, Chapter 1, Unit 1 3. PMID: 21975942

3. McGrath, J.C., Pawson, A.J., Sharman, J.L. and Alexander, S.P. (2015) BJP is linking its articles to the IUPHAR/BPS Guide to PHARMACOLOGY. Br J Pharmacol, 172, 2929-2932. PMID: 25965085

4. Benson, H., Watterson, S., Sharman, J., Mpamhanga, C., Parton, A., Southan, C., Harmar, A. and Ghazal, P. (2017) Is systems pharmacology ready to impact upon therapy development? A study on the cholesterol biosynthesis pathway. Br J Pharmacol. [Epub ahead of print] PMID: 28910500

Posted in Chemical curation

GtoPdb NAR database issue 2018: PubChem Content

The following blog post acts as supplementary data to the 2018 NAR Database Issue

GtoPdb PubChem Content

The GtoPdb PubChem integration strategy has been previously outlined (1). Since 2015 we have made nine PubChem submissions for new releases of our database. For 2017.5 (see release notes for version 2017.5) we now have 8978 Substance Identifiers (SIDs) (PubChem query “IUPHAR/BPS Guide to PHARMACOLOGY”[SourceName]). We submit within days of our public release but users should note that it can take PubChem a few days to complete the processing of a new submission and several weeks to complete the more computationally intensive relationship mappings (e.g. 3D neighbours).

It is valuable for users to be able to seamlessly navigate between bioactive chemistry content in these two resources. We therefore pay close attention to the correspondence between our internal ligand entries and the external PubChem records. For a range of technical reasons, we observe small discrepancies not only between inside and outside counts (e.g. for Compound Identifiers (CIDs)) but also the exact numbers associated with our content from derivative searches in PubChem (i.e. executed via several steps) which may depend on how the query is executed. We are in the process of investigating these minor but complex differences (including consulting with the PubChem team). In the interim we are being transparent in declaring differences between the internal counts in Table 1 and the external counts dealt with in this section.

The largest of our PubChem entries is the antisense polynucleotide mipomersen (ligand 7364) with a molecular weight (MW) of 7158. Our largest peptide entry (ligand 7387) is lixisenatide, with 44 amino acids and MW of 4858. We established that 2156 of our SIDs could not form CIDs (i.e. they had no representation in Simplified Molecular-Input Line-Entry System (SMILES) form) because they were proteins (i.e. mapped to an intact UniProtKB, large peptides or antibodies. Over the last two years we have been converting more curated peptides, and a limited number of therapeutic polynucleotides, without pre-existing CIDs, into SMILES. This enhances intra-PubChem connectivity for these increasingly important classes of ligands. To form a CID, these must be within the current upper limit of 1000 atoms, approximating to 70 residues for a peptide (Dr P Theissen, personal communication). For this reason, we have introduced the Sugar & Splice program (NextMove Software, Cambridge, UK) to facilitate our conversions of peptides to SMILES and Hierarchical Editing Language for Macromolecules (HELM) notation (15). While we have reached 273 peptide CID entries, we are continually coming up against the problem of authors insufficiently defining peptide modifications (e.g. by correct International Union of Pure and Applied Chemistry (IUPAC) terminology) for unequivocal translation to SMILES.

In Figure 1 we show an analysis of our content in PubChem.

Figure3

Figure 1. Category breakdown at the SID (A) and CID(B) level for GtoPdb PubChem entries

For the SIDs (Figure 1A), we have introduced new annotation categories into our SID comment lines for users to be able to retrieve two important subsets. These are “approved drug true” (with “true” suffixed for technical reasons; most approvals have been passed by the FDA and/or European Medicines Agency (EMA)), and “immunopharmacology” for ligands specifically curated as part of GtoImmuPdb. For PubMed links, the connections have been made by us as a source. Note also that the intersect between approved drug and immunopharmacology is derived from our curation of publications suggesting the association but are not necessarily approved for immunological clinical indications. For the CIDs, the categories in Figure 1B are as described previously (1) except for the two new ones explained above. The CID counts for these are lower than their SID counts by 160 and 334 respectively because of the antibody component of both but also peptide content of the latter. The general pattern is approximately in proportion to our 10% ligand growth over two years, with the largest increase in the PubMed coverage (expanded on below).

One of the powerful consequences of our submitting to PubChem is to be able to compare between different sources, using filters for “slicing and dicing” (2). This is already introduced in Figure 1 by showing the ChEMBL overlap, but also, in terms of complementarity, to indicate we have 1595 CID structures ChEMBL does not.

The subject of the correctness of chemical structure representation within the pharmacological domain in general and GtoPdb is too extensive to be addressed here but we have an NC-IUPHAR committee specially to advise us on this important topic. Notwithstanding we use PubChem statistics as direct quality control for the structures we submit. This can be seen in Figure 1 where we have 326 structures no other source has submitted. The converse is reassuring in that just over 95% of our structures are supported by at least one other of the 545 sources in PubChem. While this is an argument for correctness there are caveats. The first of these is that two sources can independently submit an incorrect structure. The second is that all databases have an element of circularity where records can be re-cycled between sources. Inspection of our unique structures establishes that they include extractions from the literature that (for public sources) only we have made. An example is AZ13102909 (http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=9577), where we derived the structure of a kinase inhibitor from an image in the paper (https://www.ncbi.nlm.nih.gov/pubmed/24962318/). Thus, we have introduced the additional triage of checking our unique 326 with the PubChem “same connectivity” operator to check relationships with other CIDs.

As a more detailed utility example, we generated CID comparisons to two other sources of similar size that also manually curate drugs and other pharmacologically active compounds. These are the well-established DrugBank (3) and the more recent DrugCentral (4). The former captures biochemical and pharmacological information about drugs, mechanisms and targets with recent expansion into absorption, distribution, metabolism, excretion and toxicity (ADMET). The emphasis of the latter is on active ingredients in all pharmaceutical formulations approved by the FDA and other regulatory agencies; in addition to structure and bioactivity the compounds are linked to drug label annotations and other regulatory information. The result is shown in Figure 2.

Figure4

Figure 2. Intra-PubChem content comparison between GtoPdb, DugBank and DrugCentral. The union of all three is 14892. The PubChem latest submission dates for the sources were 23rd Aug 2017, 10th Feb 2016 and 2nd Sept 2017, respectively.

The overlaps and differences between these three sources quantify their complementarity. However, exact numbers can be confounded by minor differences in chemistry rules for their independent submissions (e.g. salts, parents or both) as well as different connectivity choices for the same compound skeleton (e.g. R versus S isomer). Notwithstanding, Figure 2 makes it clear the three sources have substantially different capture. The results also establish pairwise cross-corroboration (e.g. GtoPdb overlaps with 334 and 239 structures for which DrugBank and DrugCentral, respectively, diverge between each other). It should also be noted that GtoPdb was one of the sources used in the compilation of DrugCentral which would thus contribute to the 1276 overlap (4). The three-way intersect of 1037 should correspond to those approved drugs that can form CIDs. This is lower than expected (i.e. for the FDA would be predicted to be closer to 1500) but possible reasons for this have been discussed previously (5).

 

1. Southan, C., Sharman, J.L., Benson, H.E., Faccenda, E., Pawson, A.J., Alexander, S.P., Buneman, O.P., Davenport, A.P., McGrath, J.C., Peters, J.A. et al. (2016) The IUPHAR/BPS Guide to PHARMACOLOGY in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands. Nucleic Acids Res, 44, D1054-1068. PMID: 26464438

2. Southan, C., Sitzmann, M. and Muresan, S. (2013) Comparing the chemical structure and protein content of ChEMBL, DrugBank, Human Metabolome Database and the Therapeutic Target Database. Molecular Informatics, 32 (11-12), 881-897. PMID: 24533037

3. Law, V., Knox, C., Djoumbou, Y., Jewison, T., Guo, A.C., Liu, Y., Maciejewski, A., Arndt, D., Wilson, M., Neveu, V. et al. (2014) DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res, 42, D1091-1097. PMID: 24203711

4. Ursu, O., Holmes, J., Knockel, J., Bologa, C.G., Yang, J.J., Mathias, S.L., Nelson, S.J. and Oprea, T.I. (2017) DrugCentral: online drug compendium. Nucleic Acids Res, 45, D932-D939. PMID: 27789690

5. Southan, C., Varkonyi, P. and Muresan, S. (2009) Quantitative assessment of the expanding complementarity between public and commercial databases of bioactive compounds. J Cheminform, 1, 10. PMID: 20298516

Posted in Chemical curation, Publications

Hot topic: A new research avenue investigating mitochondrial GPCR biology

As one of the first propositions for GPCRs being present in mitochondrial membranes, a recent report from Robert Friedlander and colleagues [1] follows on from previous work characterising synaptic and extrasynaptic mitochondria in human cortex (post-mortem samples) and their role in neuroprotection. This work, if reproduced, opens up new vistas, and has many implications for neurodegenerative diseases. Taken together, Suofu et al. show that melatonin is synthesised in mitochondria, that MT1 receptors are present in mitochondrial membranes, and that MT1 receptor stimulation reduces cytochrome c and caspase secretion caused by calcium overload. The authors propose that this is a mechanism for the neuroprotective effects of melatonin in hypoxic-ischaemic brain injury in neonatal and in models of Huntington’s disease, where there is mitochondrial impairment.

Comments by Michael Spedding, Secretary General, IUPHAR, and CEO, Spedding Research Solutions SARL, France

(1) Suofu Y et al. (2017). Dual role of mitochondria in producing melatonin and driving GPCR signaling to block cytochrome c release. Proc Natl Acad Sci U S A., pii: 201705768. doi: 10.1073/pnas.1705768114. [Epub ahead of print] [PMID:28874589]

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Hot topic: Crystal structure of LPA6, a receptor for lysophosphatidic acid, at 3.2A

Lysophospholipids (LPs) have myriad roles as extracellular signals that activate cognate G protein-coupled receptors (GPCRs) (2). LPs for which receptors have been reported include lysophosphatidic acid (LPA) (receptors: LPA1-6), sphingosine 1-phosphate (S1P1-5), lysophosphatidyl serine (LPS1-3, 2L (2L is a pseudogene in humans)) and lysophosphatidyl inositol/glucose (LPI/LPG), all of which are Class A GPCRs. Of these 15 LP receptors, crystal structures of two have been previously reported for S1P1 (2.8-3.35A) (3) and LPA1 (2.9-3.0A) (4) both of which utilized human cDNA sequences bound in the presence of antagonists. The new structure (1), from the laboratories of Junken Aoki and Osamu Nureki, elucidates a zebrafish receptor – with 80% amino acid similarity to human LPA6, in the transmembrane (TM) region – in the absence of a ligand, which nonetheless crystalized. This contrasts with the prior 2 antagonist-bound human structures. All 3 receptors were chimeric proteins stabilized by T4-lysozyme (S1P1 and LPA6) or thermostabilized apocytochrome b562RIL (LPA1) fused to the 3rd intracellular loop, but all were capable of responding to native ligands.

Key features of LPA6 included a surprisingly large distance between TM4 and 5, which suggests lateral entry of LPA via membrane translocation into the LPA6 binding pocket. Such a mechanism contrasts with that of LPA1 in which TM1 and 7 distances are comparatively small, and whose structure includes a barrel opening flexibly covered by an unstabilized N-terminal helix that contrasts with a stabilized helix in S1P1 that could inhibit ligand entry from extracellular space. LPA1’s structure is further consistent with LPA entry from the extracellular environment that could include its biosynthetic enzyme, autotaxin. By comparision, both S1P1 and LPA6 – despite being of distinct gene sub-families (EDG and P2Y, respectively) – show receptor entry of ligands from within the membrane plane, suggesting parallel evolution of membrane access for these gene sub-families. LPA6 prefers unsaturated LPAs (e.g., 18:2) that appear to enter a hydrophobic cleft and central cavity binding site that supports unsaturated LPA species based upon docking models. Modeling also supports LPA-binding that produces a shift of TM6 and 7 to allow more favorable interactions with LPA’s phosphate headgroup. Membrane access of LPA into LPA6 is further supported by actions of the phospholipase PA-PLA1α that was shown to increase membrane LPA without extracellular secretion, thus providing membrane ligand that could translocate into LPA6.

Comments by Jerold Chun, MD, PhD, Professor & Senior Vice President, Neuroscience Drug Discovery, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA

  1. Taniguchi, R. et al. (2017) Structural insights into ligand recognition by the lysophosphatidic acid receptor LPA6. Nature, 548, 356-360, doi:10.1038/nature23448. [PMID:28792932]
  2. Kihara, Y. et al. (2014) Lysophospholipid receptor nomenclature review: IUPHAR Review 8. Br J Pharmacol, 171, 3575-3594, doi:10.1111/bph.12678 . [PMID:24602016]
  3. Hanson, M. A. et al. (2012) Crystal structure of a lipid G protein-coupled receptor. Science, 335, 851-855, doi:10.1126/science.1215904 . [PMID:22344443]
  4. Chrencik, J. E. et al. (2015) Crystal Structure of Antagonist Bound Human Lysophosphatidic Acid Receptor 1. Cell, 161, 1633-1643, doi:10.1016/j.cell.2015.06.002 . [PMID:26091040]
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Hot topic: FZD6 dimers dissociate after stimulation – briefly

GPCRs of all classes are widely thought to form homodimers, heterodimers and higher-order oligomers. The functional significance of dimerization is well understood for Class C receptors but less certain for the other GPCR classes, including the rather unconventional class F or Frizzled (FZD) receptors. Although the relationship between receptor activity and quaternary structure is often unclear, across classes it is generally found that ligand binding does not dramatically influence dimerization. A recent report by Gunnar Schulte and his colleagues suggests that in this respect class F receptors may once again be somewhat different [1]. Using an impressive combination of live-cell imaging, biochemical and modeling techniques the group presents evidence that FZD6 forms relatively stable dimers that dissociate when stimulated with the activating ligand WNT-5A. Remarkably, FZD6 protomers reassociate at the cell surface after 20 minutes of continuous stimulation, a timing which coincides with termination of ERK1/2 phosphorylation. Taken together with previous results from the Schulte group [2] the data are consistent with a model where FZD6 dimers are constitutively associated with G proteins and the phosphoprotein Disheveled (DVL) in an inactive state complex that must dissociate in order to generate downstream signals. Although it remains to be seen how representative this model will be for other GPCRs, including other class F receptors, the report sets an important standard for studies aimed at linking receptor activity and quaternary structure.

Comments by Nevin A. Lambert, PhD, Department of Pharmacology and Toxicology Medical College of Georgia, Augusta University, USA

[1] Petersen, J., Wright, S.C. et al. (2017) Agonist-induced dimer dissociation as a macromolecular step in G protein-coupled receptor signaling. Nat Commun. 8(1):226.  [PMID: 28790300]

[2] Kilander, M.B.C., Petersen, J. et al. (2014) Disheveled regulates precoupling of heterotrimeric G proteins to Frizzled 6. FASEB J. 28(5):2293-305. [PMID: 24500924]

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Hot topics: A cryptic binding pocket in K2P2 exposes new avenues for drug development.

The TREK subfamily of K2P channels (K2P2, K2P4 and K2P10) pass background potassium currents that modulate the excitability of neuronal cells and cardiac myocytes. In recent years, these channels have received significant attention as potential drug targets. This is in part because of their proposed roles in the regulation of nociception, analgesia, anesthesia and depression and, also because they act as polymodal signal integrators for physiological influences as diverse as temperature, membrane tension, phosphorylation, and phospholipids [1-3]. However, despite accelerating progress, including atomic resolution structures of two TREK subfamily members [4,5] , and K2P1 [6], a deeper appreciation of how K2P channel structure-function relationships, including gating mechanics, relate to physiology and disease remains hampered by a paucity of specific blockers and activators. In an elegant new study, Lolicato and colleagues from the Minor lab highlight the synergistic power of combining structural and functional approaches to reveal new insights into the operation of membrane proteins and unveil a new avenue for the development of TREK-channel pharmacology [7].
Lolicato et al., describe crystal structures of mouse K2P2 (TREK1) in complex with a novel K2P2-specific activator (ML335), and a K2P10 activator (ML402) [7]. ML335 and ML402 occupy a previously unidentified binding site—the K2P modulator pocket. Like all K2P channels, K2Ps 2, 4 and 10 are composed of two subunits, each with two pore domains and can assemble as homomers or heterodimers. Given the bilateral nature of the K2P structure, each channel will have two modulator pockets. The modulator pocket is located between the P1 and M4 helical domains in each subunit where residues conserved among TREK subfamily channels interact with the ML335 and ML401 via cation-π and π-π interactions.

While the activity of most ion channels is controlled by multiple gates, experimental evidence has accumulated to support the idea that K2P channels use a single C-type gate at the outer pore which controls ionic flux by the mechanics of the selectivity filter for potassium ions [8-10]. Numerous studies suggest that the unique architecture of K2P channels routes diverse regulatory signals to the C-type gate to control channel activity [9,11-13]. Thus, operation of the C-type gate is directly sensitive to changes in the permeant ion [11,13] and indirectly influenced by various K2P channel regulators that interactions with domains that in-turn impact the C-type gate [12-16]. The modulator pocket described lies behind the selectivity filter. Functional studies show that ML335 holds the pocket in an open conformation and thereby, activates the channel by stabilizing the C-type gate of K2P2 [7]. Because modulator pocket activators appear to be sufficient to open K2P2 channels, the findings suggest that this previously unappreciated, druggable site can be leveraged for the development of novel channel gating-modulators with potential utility as analgesics, anesthetics or neuroprotective agents.

Comments by Leigh D. Plant, Ph. D. (Research Associate Professor, School of Pharmacy, Northeastern University)

References
[1] Goldstein, S. A. et al. (2001). Potassium leak channels and the KCNK family of two-P-domain subunits. Nat Rev Neurosci 2, 175-184. [PMID: 11256078</a].

[2] Enyedi, P. & Czirjak, G. (2010). Molecular background of leak K+ currents: two-pore domain potassium channels. Physiol Rev. 90, 559-605. [PMID: 20393194].

[3] Honore, E. (2007). The neuronal background K2P channels: focus on TREK1. Nat Rev Neurosci. 8, 251-261. [PMID: 17375039].

[4] Brohawn, S. G., del Marmol, J. & MacKinnon, R. (2012). Crystal structure of the human K2P TRAAK, a lipid- and mechano-sensitive K+ ion channel. Science, 335, 436-441. [PMID: 22282805].

[5] Dong, Y. Y. et al. K2P channel gating mechanisms revealed by structures of TREK-2 and a complex with Prozac. Science, 347, 1256-1259. [PMID: 25766236].

[6] Miller, A. N. & Long, S. B. (2012) Crystal structure of the human two-pore domain potassium channel K2P1. Science, 335, 432-436. [PMID: 22282804].

[7] Lolicato, M. et al. (2017). K2P2.1 (TREK-1)-activator complexes reveal a cryptic selectivity filter binding site. Nature, 547, 364-368. [PMID: 28693035].

[8] Zilberberg, N., Ilan, N. & Goldstein, S. A. (2001). KCNKØ: opening and closing the 2-P-domain potassium leak channel entails “C-type” gating of the outer pore. Neuron, 32, 635-648. [PMID: 11719204].

[9] Piechotta, P. L. et al. (2011). The pore structure and gating mechanism of K2P channels. EMBO J, 30, 3607-3619. [PMC: PMC3181484].

[10] Schewe, M. et al. (2016). A Non-canonical Voltage-Sensing Mechanism Controls Gating in K2P K(+) Channels. Cell 164, 937-949. [PMID: 26919430].

[11] Cohen, A., Ben-Abu, Y., Hen, S. & Zilberberg, N. (2008). A novel mechanism for human K2P2.1 channel gating. Facilitation of C-type gating by protonation of extracellular histidine residues. J Biol Chem, 283, 19448-19455. [PMID: 18474599].

[12] Bagriantsev, S. N., Clark, K. A. & Minor, D. L., Jr. (2012). Metabolic and thermal stimuli control K(2P)2.1 (TREK-1) through modular sensory and gating domains. EMBO J, 31, 3297-3308. [PMC: PMC3411076].

[13] Bagriantsev, S. N. et al. (2011). Multiple modalities converge on a common gate to control K2P channel function. EMBO J, 30, 3594-3606. [PMID: 21765396].

[14] Chemin, J. et al. (2005). A phospholipid sensor controls mechanogating of the K+ channel TREK-1. EMBO J, 24, 44-53. [PMID: 15577940].

[15] Murbartian, J., Lei, Q., Sando, J. J. & Bayliss, D. A. (2005). Sequential phosphorylation mediates receptor- and kinase-induced inhibition of TREK-1 background potassium channels. J Biol Chem, 280, 30175-30184. [PMID: 16006563].

[16] Honore, E., Maingret, F., Lazdunski, M. & Patel, A. J. (2002). An intracellular proton sensor commands lipid- and mechano-gating of the K(+) channel TREK-1. EMBO J, 21, 2968-2976. [PMID: 12065410].

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Anti-infective pilot entries

GtoPdb has been traditionally focused on the pharmacology associated with human diseases (i.e. we have not been funded to cover anti-infectives).  In 2017 we have been exploring possible funding opportunities to extend into  expert curation of anti-infectives, particularly in the light of the antibiotic resistance threat and expanding drug discovery efforts for neglected tropical diseases (NTDs).  Consequently, for this release we have added a selection of entries as a proof of concept for how well our current data model would accommodate these new types of relationship mappings “off the bat”.  These are now under a new  category of “Anti-infective targets“.  A snapshot of the six new entries is show below.

Capture

We curated three antimalarials,  two antivirals and one antibiotic, some of which have the ligand in PDB entries. By and large,  this pilot was successful and we would be pleased to get feedback from interested parties.  A number of technical challenges were encountered  but most of these were “domain inherent” rather than GtoPdb data model issues per se.  Examples include the sub-species and strain multiplexing of the target sequences. This results in having to map the authors described ligand activity data to TrEMBL entries (sometimes with equivocalities as to the exact isolate sequence) rather than to the deeper annotated Swiss-Prot entries avaialble for some reference pathogen proteomes with completed gene naming.  We also ran in to the multi-enzyme “string of pearls” problem where large polypeptides encode for multiple  functional domains, more than one of which that can be (or have been) targeted by different inhibitors.  Classically, this is the case for the viral polyprotein precursor proteins but in this set also for the polyketide synthase entry shown below.

Capture

This was derived from a recent 2017 Cell paper  “Development of a Novel Lead that Targets M. tuberculosis Polyketide Synthase 13” (PMID 28669536). Should we be sucessful in being resourced to expand in this domain we can already envisage tweaks to our existing data model and curation processes that could address some these domain-specific challenges.  For example,  we can specify ligand-targeted domains not only by InterPro coordinates in UniProt entries but also by getting the TrEMBL entries “promoted” to Swiss-Prot to enhance the domain annotation cross-references.

 

Posted in Uncategorized

New source cross-references in release 2017.5

(minor updates 15 Sep 2017)

The statistics of content are presented as usual in the release notes and The Guide to IMMUNOPHARMACOLOGY has a separate update.  This post describes changes and updates to other resources we provide links to, that have been introduced in this release cycle.  More detail will be provided in the help pages (and feedback on any of them is welcome) but the outlines are as follows;

Extra links for ligands. The new connectivity applies to those that have chemical structures (i.e. SMILES strings for mostly small molecules but also peptides up to ~ 50 to 60 residues and a few oligonucleotide drugs), which represents 6821 ligands in GtoPdb. Links have now been rationalised by introducing InChIKey call-outs to UniChem at the EBI.  This resource, currently containing over 150 million indexed chemical structures from 37 sources (including our own), many of which we had hitherto individually curated links for.  In essence, UniChem “looks after” comprehensive cross-mappings between these sources via a regular and precise automated process. We can consequently rely on presenting these links for our own entries. This is because we have selected and curatorially checked (i.e. locked-down) our own structural assignments, including for our PubChem submissions.  By clicking the UniChem link users can now quickly navigate to complementary sources  such as  DrugBank, ChEBI, HMDB, BindingDB, ChEMBL, PDBe SureChEMBL (patents) and others. Note this is analogous to the Google InChIKey call out we already introduced for our ligands some time ago. There is some overlap in the result sets but note the Google search will find different chemistry sources (including ChemSpider entries, usualy uppermost in the Google rankings) that are not currently indexed by UniChem.

The Human Protein Atlas (HPA) team have increased their profile recently,  not only by becoming one of the European ELIXIR core resources but also because of a major new extension in the form of a Pathology Atlas with a focus on human cancer.  We have also had contacts with the team.  Consequently,  we selected this as as a new outlink from our human protein entries (2839 target links and 353 ligand links) as an excellent first-stop shop for tissue and cell line expression patterns as well as intracellular distributions.  In terms of utility it is important to note that HPA offers the best of both worlds by integrating three sources of high-throughput mRNA transcript profiling in addition to direct antibody detection of the protein.

CATH/Gene3D. As you may have been noticed we have increased our protein structure connectivity in 2017 including our SynPharm drug-responsive protein sequences resource (see below).  There are many user utilities for the increase in structural data, including the impressive acceleration of ligand binding sites resolved in new GPCR structures. CATH is a classification of PDB protein structures grouped by protein domains into superfamilies that have diverged from a common ancestor. Users are encouraged to take a look at the  features of CATH for their own exploitation. These include tracking the deep phylogeny of pharmacological targets (that have structures) where this is difficult to detect on the basis of sequence similarity alone. The current version of GtoPdb includes 1634 target links to CATH (which is lower than the total because not all protein families have 3D structural representation, yet), and 230 peptide ligands  (Sep 2017 update CATH is also now European ELIXIR core resources).

synPHARM was originally set-up to provide synthetic biologists with tools to discover sequences that could be modulated by known ligands from GtoPdb which could be transferred to synthetic proteins in order to confer drug control. synPHARM combines structural information from the Protein Data Bank with information on ligand binding from GtoPdb to produce a database of ligand binding sequences. As such, it is a useful resource for 3D ligand binding information. We have now added links from GtoPdb target and ligand pages to structures in synPHARM.

IUPHAR Pharmacology Education Project (PEP). PEP is a new IUPHAR initiative to provide free access to education and training resources in pharmacology. We have added links from 673 ligand and drug pages to background information in PEP, for further information on drug action and clinical use.

RCSB Protein Data Bank (RCSB PDB). Although not strictly new, it’s worth pointing out that the current rate of reporting new structures of ligands bound to targets means the number of links to the PDB via ligand entries has increased significantly over recent releases. The number of our PDB ligand links now stands at 1337, based on exact InChIKey matches. In addition, many of the GtoPdb ligands are represented in the PDB as alternative isomeric forms. Note also there are occasions where the PubChem MMDB CID assignment does not exactly match the PDB ligand structure.  In both these cases we add cross-pointers in the ligand comment sections.

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Database release 2017.5

The 5th IUPHAR/BPS Guide to PHARMACOLOGY database release of 2017 includes updates to several target families, and new targets and ligands added, focusing on those relevant to immunopharmacology. We also announce a new organisation for ligand families and groups. This update also includes the beta v2.0 release of the IUPHAR Guide to IMMUNOPHARMACOLOGY portal taking into account early feedback from our beta testers. Eagle-eyed users may have noticed a new homepage layout for GtoPdb, which has been reorganised to highlight important new features at the top of the page, with quick links to the main database pages on the left, and news items and publications below.

Target and ligand updates

Ligand families

We have introduced a new organisation of peptide ligands into families. This can be reached via a link from the “Ligands” submenu of the main navigation menu. This started with the aim of grouping related peptide sequences together into families to aid discoverability and allow us to add comments and references pertaining to the family as a whole. We have also experimented with grouping together some other types of ligands (such as the Immune checkpoint modulators) linked by their mechanism of action (although not a family in the phylogenetic sense). Feedback on this new organisation is welcome.

Ligand activity graphs

Continuing on from previous updates (releases 2017.2 and 2017.4), where we described the addition of graphs to visualise ligand activity data for targets across species using data from GtoPdb and the med-chem database, ChEMBL, we have now extended this feature to all ligands in GtoPdb with quantitative activity data at targets, even where the ligands do not have data in ChEMBL. There will  also be cases where the GtoPdb curators just haven’t yet identified the ligand in ChEMBL, in particular peptides can be difficult to search for because of naming differences and lack of standard chemical structure descriptors.

Expanded database cross-links

From time to time we internaly review the databases that we cross-link to and from, to make sure they are current and useful. During an iteration of this process within this release cycle we introduced several new resources that have value for users. These changes are explained in a separate post.

IUPHAR Guide to IMMUNOPHARMACOLOGY beta v2.0

This update also sees the release of the beta v2.0 of the new Guide to IMMUNOPHARMACOLOGY portal. This is a Wellcome Trust-funded extension to the existing database, aiming to improve data exchange between immunology and pharmacology. Read the release notes and technical update here. We are grateful for all the feedback received so far and welcome continued comments and bug reports as we further develop the new data and portal.

Database content and statistics

For the full statistics on release 2017.5 please see the about page on the GtoPdb site. In summary, there are now 15,281 curated binding constants between 2825 targets and 8978 ligands. (N.B. for various reasons, not all those targets and ligands have  quantitative binding data; in the third table below the current number of human targets with quantitative data is 1431.)

db_contentstats

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Guide to IMMUNOPHARMACOLOGY – beta release v2.0, August 2017

We are please to announce the second, beta-release of the Wellcome Trust-funded IUPHAR Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb). Since our first beta-release back in May 2016, we have undertaken a user-testing exercise to gather feedback on the layout, navigation and content of the resource. This blog post summarises the outcomes from the user-testing and the consequent changes in the v2.0 release.

User Testing

We reached out to several groups of immunology and inflammation researchers asking for anyone interested in helping us to test the GtoImmuPdb beta v1.0 release. These groups came from the British Society of Immunology, Glasgow University, the IUPHAR ImmuPhar Section and more. We set-up a google form to guide people through using the beta site and asked relevant questions about each section of the site, focussing on how easy the site was to use, how credible the data appeared to be and what features users would like to see added/removed. In total 8 paritipants compelted the testing, and these testers had a variety of research experience (PhD student to Professor) and previous experience of the using GtoPdb (from several visits a month to never having used it before).

Some of the key outcomes have informed changes in the v2.0 release. Most notably, reorganisation of help documentation, altering process/cell type layouts and navigation and improving information on disease associations.

Website Updates

Help Pop-ups

Help pop-ups have been added to the main panels on the portal. This gives upfront help about what users can expect to find within each section, and how to navigate it. We believe this is easier than having to read through a tutorial or help page. Our aim will be to supplement these with short help videos, showing how to navigate the data.

From our user feedback, although help was easy enough for most user to find, some comments pointed to it not always being immediately obvious what the data being displayed was and how to navigate it. We hope that by adding in ‘in-line’ help pop-ups it is easier and quicker for users to find the relevant guidance.

Help pop-ups added to portal

Process/Cell type layout 

We have made some minor modifications to the layout of both the process association and cell type association pages. The navigation menus (pull-down menu and quick links to target class sections) have been swapped over.

We have also added in a simple piece of javascript to display a ‘back to top’ button if the users scrolls down the page. This should help navigation. This feature may eventually be re-used in other parts of the site.

Revised layout of process association pages. Navigation items have been moved and new ‘return to top’ button is present on scroll-down

Improvements to disease layout – response to feedback

Our user-testing highlighted the need to display more information on the disease association pages, particularly about why ligands are associated with some diseases. The information displayed has been extended to show whether the ligands is an approved drug (and which regulator it was approved by) and links to more info at drugs.com. We have also added the clinical use comments for the ligand. This is all data that can be found on the ligand summary pages, but we have also surfaced into on the disease association pages to bring added value and ensure the most relevant information is available in the right places.

Additional information including if ligands are approved drugs and clinical use comments bring added value

Further reading – exposing useful curation reading list

A new page has been added that presents a further reading collection extracted from an open CiteUlike collection compiled by the curation team http://www.citeulike.org/tag/immpharm. The papers presented are general, not ones from which database entries have been curated. They are mostly review articles that are relevant to the scope of the database. We would be pleased to receive recommendations for additions (either to the further reading list or for curation).

Listing papers of relevance to immunopharmacology that are not already used in curated entries

Future priorities

Other aspects of the process and cell type data commented on during user-testing was the need for more information on GO terms, IDs and evidence; the need to incorporate curator comments about the process associations; and the absence of data for some cell type categories. Improving the content and display to meet these is a priority, but a substantial body of curatorial work. So we will be aiming to meet these needs, but not until future releases.

Development of the beta-release is ongoing with regular updates planned over the next few months as the quantity of data captured increases and improvements in the site layout and function are made. As always we welcome comments and engagement with interested user groups and  potential future users, so don’t hesitate to get in touch with us.

This project is supported by a 3-year grant awarded to Professor Jamie Davies at the University of Edinburgh by the Wellcome Trust (WT).

Posted in Guide to Immunopharmacology, Technical

Hot topics: Agonist-bound crystal structures of the CB1 cannabinoid receptor

Antagonist bound crystal structures of GPCRs are useful in giving an insight into the molecular conformation of a receptor’s inactive state whilst enabling the design of new drugs. However, they prove insufficient to understand the activation mechanism of the receptor and mediation of its physiological effects. This necessitates the study of agonist-bound structures. In this direction, Hua et al., (2017) [1] have recently reported two agonist-bound crystal structures of Cannabinoid Receptor 1 (CB1), one with a tetrahydrocannabinol derivative, AM11542 [PDB: 5XRA], and the other with a hexahydrocannabinol, AM841 [PDB: 5XR8]. Previously, two antagonist-bound crystal structures of CB1 complexed with AM6538 and MK-0364 (taranabant) were reported by Hua et al., (2016) [PDB: 5TGZ] [2] and Shao et al., (2016) [PDB: 5U09], respectively [3].

Comparing the agonist and antagonist bound structures of the CB1 receptor reveals significant details:

1. The N-terminus in 5TGZ and 5U09 is a V-shaped loop which interacts with the bound antagonists, acting like a plug to the orthosteric binding pocket. The agonist-bound versions (5XRA and 5XR8), however, have their N-terminus residing over the binding pocket without any direct involvement in ligand binding. However, the N-terminus is truncated in all the crystal structures and hence the authors do not rule out the possibility that the full-length N-terminus might assume an entirely different conformation.

2. Both the agonists adopt an L-shaped conformation in the binding pocket, in contrast to the horizontal geometry of AM6538 in 5TGZ. The helical rearrangements hence observed in TM 1 and 2 and inward movement of residues Phe1702.57 and Phe1742.64 lead to a reduction in the binding pocket volume by 53% compared to 5TGZ. This serves as a testament to the highly flexible nature of the CB1 receptor and should be considered in future structure-based drug design studies for the receptor.

3. The alkyl chain of the two agonists extends into the ‘long channel’ of the receptor formed by the transmembrane helices (TM) 3, 5 and 6. The authors point out that this orientation is similar to that of ‘arm 2′- the nitroalkyl region of AM6538 in 5TGZ and of the alkyl chain of ML056 in the previously-described structure of the S1P1 receptor [4], thus indicating that the long channel could be a conserved binding region for alkyl chains in lipid binding receptors.

4. In 5TGZ and 5U09, the residues Phe2003.36 and Trp3566.48 exhibit aromatic stacking with each other. In this report, a synergistic conformational change of the residues was observed with the rotation of TM3 and side chain flip of Phe2003.36 towards the binding pocket occurring simultaneously with the rotation of TM6 away from TM3 breaking the interaction between the residues. The authors speculate the role of this ‘twin toggle switch’ in the activation of the receptor as a previous study has already shown [5].

5. Using the crystal structure, a cholesterol molecule has been identified to bind between the cytoplasmic portions of TM 2, 3, and 4 in the agonist-bound models. This was not observed in the antagonist models. However, the possible existence of a lipid access channel proposed in the taranabant bound (5U09) structure has not been discussed in this paper. This raises questions about the influence of lipids on the receptor binding through allosteric sites.

Comments by Lahari Murali (@wavesml), Steve Alexander (@mqzspa), Steven Doughty and Abi Emtage (@AbiEmtage)

[1] Hua, T. et al. (2017). Crystal structures of agonist-bound human cannabinoid receptor CB1. Nature.doi:10.1038/nature23272. [PMID: 28678776]

[2] Hua, T. et al. (2016). Crystal Structure of the Human Cannabinoid Receptor CB1. Cell 167: 750–762.e14. doi: 10.1016/j.cell.2016.10.004. [PMID: 27768894]

[3] Shao, Z. et al. (2016). High-resolution crystal structure of the human CB1 cannabinoid receptor. Nature 540:602–606. doi: 10.1038/nature20613. [PMID: 27851727]

[4] Hanson, M. A. et al. (2012). Crystal structure of a lipid G protein-coupled receptor. Science 335:851–855. doi: 10.1126/science.1215904. [PMID: 22344443]

[5] Singh, R., Hurst, D.P., Barnett-Norris, J., Lynch, D.L., Reggio, P.H., and Guarnieri, F. (2002). Activation of the cannabinoid CB1 receptor may involve a W6 48/F3 36 rotamer toggle switch. J. Pept. Res. 60: 357–370. [PMID: 12464114]

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Hot topics: Identifiers for the 21st century

While identifiers are not a traditional “hot topic” in pharmacology the subject is becoming increasingly important. One of the reasons is that for mechanistic pharmacology the community needs to define (and communicate) identifiers for the key entities of model organism species and strains, proteins, protein complexes, genes, sequences, sequence variants, as well as the explicit molecular structures of chemicals, peptides and therapeutic biologicals (including antibodies) used for experimentation. Indeed one of the roles of IUPHAR (as NC-IUPHAR) is to review and recommend protein target nomenclature, in collaboration with the Human Gene Nomenclature Committee (HGNC) [1]. The paper featured here is a technical review [2] of identifier qualities and best practices that facilitate large-scale data integration. It also goes into problems related to persistence and web-accessibility/resolvability. As a database provider, the relevance of this article for GtoPdb is clear (since we are largely about identifiers and their relationships). We are carefully considering its implications and possible consequent changes in our practice. The GtoPdb team has already engaged with this theme some time ago in a blog post [3] that provided an introduction to resolving bioactive ligands and their protein targets from the literature to standardised molecular identifiers.

Comments by Chris Southan (@cdsouthan).

[1] International Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification http://www.guidetopharmacology.org/nciuphar.jsp

[2] McMurray et al. (2017). Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data. PLoS Biol. 29;15(6). [PMID:28662064].

[3] A Pharmacologists’ Guide to Resolving Chemical Structures and their Protein Targets from the Literature https://blog.guidetopharmacology.org/2014/11/11/a-pharmacologists-guide-to-entity-resolution/

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Hot topics: X-ray crystal of the apelin receptor

Activation of the apelin receptor by the peptides apelin or Elabela/Toddler mediates vasodilatation and positive inotropic effects in the adult cardiovascular system and knocking out the receptors results in failure of the heart to develop in developing embryos. To date, only a limited number of Family A structures (including opioid, endothelin ETB, and orexin OX1 and OX2) have been deduced using X-ray crystallography. Ma et al., (2017) have recently reported the 2.6-Å resolution crystal structure of human apelin (APJ) receptor in complex with a synthetic 17-amino-acid apelin analogue agonist. The authors identify a two-site ligand binding mode that has not been seen in previous solved Family A receptor structures. The structure is in reasonable agreement with studies using NMR (Langelaan et al 2013) and molecular dynamics simulations (Macaluso and Glen 2010, Yang et al, 2017) In addition, many of the key interfacial receptor:agonist residues identified from the crystal structure are in agreement with mutation data on apelin binding. However, it is worth noting the following caveats that make interpretation of the data difficult:

1. Residues were removed from the N-terminus (residues 1–6) and C terminus (residues 331–380).

2. A putative glycosylation motif at N175 was eliminated from ECL2. It is an open question as to whether glycosylation affects agonist binding in the apelin receptor.

3. Two putative palmitoylation sites were removed from TM8. Again, it is an open question as to whether palmitoylation affects agonist binding in the apelin receptor.

4. To achieve crystallization, mutations V117A and W261K were introduced. These force the intracellular portion of the receptor into the inactive state. In fact, these mutations seem to render the receptor unable to bind apelin-13.

5. The synthetic 17-amino-acid apelin analogue agonist is significantly different from the apelin sequence. In particular, a macrocycle and significant mutations have been introduced, which may alter the peptide conformation and its interactions.

6. The crystal structure is unable to explain the importance of the Arg2 and Leu5 residues of apelin 13, which are known to be key binding elements from mutation data.

Despite these caveats, the crystal structure provides much needed data on the apelin receptor. A key question in the apelin field is why two peptides have evolved binding to the same ligand in mammals. Although the authors did not report binding with Elabela/Toddler analogues, the initial structure will foster understanding whether these two ligands differ in signalling mechanisms. Intriguingly, Lena et al (2017) have identified a key role for Elabela/Toddler in preeclampsia but this may not be mimicked by apelin suggesting spatiotemporal differences in signalling.

Comments by Anthony Davenport, David Huggins, Janet Maguire, and Robert Glen.

Ma et al. (2017) Structural Basis for Apelin Control of the Human Apelin Receptor. Structure. 6:858-866.e4. [PMID:28528775]

Langelaan et al. (2013) Structural features of the apelin receptor N-terminal tail and first transmembrane segment implicated in ligand binding and receptor trafficking. Biochim Biophys Acta. 1828:1471-83. [PMID:23438363]

Macaluso NJ, Glen RC. (2010) Exploring the ‘RPRL’ motif of apelin-13 through molecular simulation and biological evaluation of cyclic peptide analogues. ChemMedChem. 8:1247-53. [PMID:20486151]

Yang P et al. (2017) Elabela/Toddler Is an Endogenous Agonist of the Apelin APJ Receptor in the Adult Cardiovascular System, and Exogenous Administration of the Peptide Compensates for the Downregulation of Its Expression in Pulmonary Arterial Hypertension. Circulation. [PMID:28137936]

Lena et al. (2017) ELABELA deficiency promotes preeclampsia and cardiovascular malformations in mice. Science DOI. 10.1126/science.aam6607

 

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HGNC gene links to GtoPdb

As regular users of GtoPdb will be aware, our target pages include HUGO Gene Nomenclature Committee (HGNC) gene symbols, nomenclature and links to HGNC gene pages (Fig 1).

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Figure 1. GtoPdb gene information including link outs to HGNC pages by clicking on the human gene symbol.

HGNC pages in turn link back to GtoPdb target pages under the “Specialist database” link (Fig 2).

hgnc_target_link

Figure 2. HGNC gene page showing the link to the IUPHAR/BPS Guide to Pharmacology (GtoPdb) under “Specialist Databases”.

In GtoPdb release 2017.4 there were 2823 HGNC target links. In June 2017 we also added a further 430 HGNC links to GtoPdb peptide ligand pages (Figs 3 and 4). These are either small proteins such as cytokines, or endogenous peptides derived from Swiss-Prot proteins that have an HGNC entry. Implicit in our classification as ligands these will have (in most cases quantitative) reported interactions with cognate receptors.  The peptides will usually correspond to sequences processed from their precursor proteins in HGNC (e.g. the eight angiotensin peptides from Angiotensinogen, AGT).  Note that some of these peptides are cross-linked to other ligand entries which are similar synthetic bioactive sequences that do not exactly match the cleavage cross-references in UniProt.

ligand_gene

Figure 3. GtoPdb peptide ligand page which links to the HGNC gene page by clicking on the gene symbol.

hgnc_ligand_link

Figure 4. HGNC gene page for a chemokine ligand showing a link to the GtoPdb ligand page.

For over 50 genes which encode multiple mature peptides, the HGNC page links to the longest peptide sequence included in GtoPdb. This is because HGNC currently only supports one external link per resource, and they are working on providing support for multiple links by the end of this year.

This expansion was driven by importance of these reciprocal links for HGNC users to navigate across to pharmacolgical information. In addtion, going the other way, they enable GtoPdb users to find out more about gene nomenclature and other genetic information via HGNC.

The full list of HGNC in-links to GtoPdb can be downloaded here (as a CSV file as illustrated in Fig 5). Ligand links can be distinguished from target links by the URL.

genes

Figure 5. Part of the CSV file containing all the HGNC links to GtoPdb showing some of the new ligand links.

 

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Hot topic: Activity-based protein profiling reveals off-target proteins of the FAAH inhibitor BIA 10-2474

The historical context for this commentary can be found in this blogpost. This latest report, based on activity-based profiling (ABPP), constitutes the first open biochemical investigation of BIA 10-2474 (1). The ABPP results show it inhibits several lipases that are not targeted by PF04457845, a highly selective and clinically tested FAAH inhibitor. In addition BIA 10-2474 (but not PF04457845) produced substantial alterations in lipid networks in human cortical neurons. The authors are appropriately cautious in not over-extrapolating their findings to causality of pathology recorded in the unfortunate patients (see clinical report in PMID 27806235). However, biochemical and pharmacological questions still remain. One of these is that, given the initial binding interaction is no less than three orders of magnitude lower that PF004457845, it’s not entirely clear why 10-2474 was chosen as the lead. Another question is the basic kinetic parameters for purified enzymes (not just crude cell extracts in vitro) are still not available. This should include at least two methods for confirming irreversibility (e.g. IC50 vs pre-incubation or using a 10-2474 radiolabeled derivative). Word has it that a BIAL paper is in preparation so this aspect might be addressed by new results. Note also there are now two compound suppliers in PubChem offering BIA 10-2474 so more experimental reports could be expected.

The GtoPdb entries below have been updated with key interactions from this paper and will go live at the next release.

BIA 10-2474

PF004457845

FAAH

FAAH2

(1) van Esbroeck ACM et al. (2017). Activity-based protein profiling reveals off-target proteins of the FAAH inhibitor BIA 10-2474. Science, 356(6342): 1084-1087 [PMID:28596366]

Comments by Chris Southan (@cdsouthan)

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Hot topic: GPR3 and GPR6, novel molecular targets for cannabidiol

Cannabidiol is a major metabolite from the Cannabis plant, although levels vary dependent on genetic, regional, cultivation and other factors.  It lacks the psychotropic nature of THC, but has been reported to have many biological effects, to the extent that clinical trials for infantile intractable epilepsy are currently ongoing in the US. GPR3 and GPR6 are orphan GPCRs, which have previously been reported to elevate cAMP levels constitutively when expressed in recombinant systems.  Although there was some evidence for activation by sphingosine 1-phosphate, this was not reproduced.  In this report, a number of endogenous and Cannabis-derived metabolites were examined for their effects on β-arrestin2 recruitment in cells expressing either GPR3 or GPR6.  Of these agents, only CBD caused a reduction in β-arrestin2 recruitment in a concentration-dependent manner, with pIC50 values of 5.9 and 6.7 at GPR3 and GPR6, respectively.  The authors suggest that the inverse agonist nature of CBD at these receptors might be of relevance for neurodegenerative disorders, such as Parkinson’s and Alzheimer’s Disease.

Comments by Steve Alexander (@mqzspa)

(1) Laun AS, Song ZH. (2017) GPR3 and GPR6, novel molecular targets for cannabidiol. Biochem Biophys Res Commun. 2017 May 29. pii: S0006-291X(17)31074-4. doi: 10.1016/j.bbrc.2017.05.165. [Epub ahead of print] [PMID:28571738]

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Hot topic: Selectivity determinants of GPCR–G-protein binding

As a detailed comparative sequence/structure/evolution analysis it is relatively unusual (in a good sense) to see such a bioinformatics article in Nature. This tour de force was a collaboration between MRC Laboratory of Molecular Biology, Cambridge UK and the Department of Drug Design and Pharmacology, University of Copenhagen (home of the GPCRdb team). As we know, GPCR signal transduction involves the binding of ligand-activated receptors to their appropriate Gα proteins. In this work selectivity-determining positions for signal transduction (as structural “barcodes”) were inferred by comprehensively comparing the sequence conservation between paralogues and orthologues, incorporating information from recent structures. The residue positions for the interaction interfaces are collated and presented at gpcrdb.org (tab ‘Signal Proteins’) for all human receptors and their 16 Gα proteins. This will be updated (including data from new structures) as a guide to interface determinants of coupling selectivity. Many applications of this resource can be envisaged. These could include: exploring options to target GPCR-G protein interfaces with agents that block coupling between the receptor and G protein intracellularly, protein engineering, structural studies and understanding the consequences of natural variation or rare disease associated mutations occurring in the vicinity of the barcode positions.

Note that all GtoPdb GPCRs have cross-references to GPCRdb (who we collaborate with) so users can navigate structural data (including the barcode positions) via GPCRdb, but also exploit ligand-centric navigation via GtoPdb and links out to genomic variants via the Ensembl links.

[1] Flock et al. (2017). Selectivity determinants of GPCR-G-protein binding. Nature, 545: 317-322. [PMID:28489817].

Comments by by Chris Southan (@cdsouthan)

 

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Hot topics: Crystal structure of full-length glucagon receptor provides insight into relative orientation of extracellular and transmembrane domains in an inactive conformation and importance of dynamic changes in this orientation for activation

It has been quite challenging to gain high resolution structural insights into an intact class B G protein-coupled receptor, despite previous solution of multiple structures for the two dominant domains, the extracellular domain (ECD) and the transmembrane helical bundle domain (TMD) of this family of receptors. Zhang et al. (1) now report a crystal structure of full length glucagon receptor (GCGR) in an inactive conformation stabilized by the non-peptidyl antagonist, NNC0640, and mAb1, bound to the ECD. In this new structure, the ECD is elongated above the TMD, with mAb1 resting on extracellular loop 1 (ECL1), and with the stalk region that links the two dominant receptor domains present in a β-strand conformation lying across the helical bundle between ECL1 and ECL2/ECL3. Of particular interest, hydrogen bonds are formed between the stalk and ECL1 to establish a compact β-sheet. The conformation of the stalk in this structure is different from the α-helical extension of TM1 present in the previous solved structure of the isolated ECD of this receptor (2), with the orientation of the ECD in the new structure quite different from that previously predicted. The authors used data from hydrogen-deuterium exchange, disulfide crosslinking, and molecular dynamics to suggest that the relatively stable β-sheet formed by the stalk and ECL1 plays an important role in controlling accessibility of the orthosteric peptide ligand to its site of docking and in the transition of inactive to active receptor states. A hypothetical model is proposed whereby the C-terminus of glucagon gains access to the peptide-binding groove within the ECD, a step that requires ECD separation from the stalk/ECL1 complex, with this initial ligand-binding event leading to a conformational change in the receptor that is not yet understood, allowing the N-terminus of glucagon to dock within the TMD to activate the receptor. A recent report of the use of cryo-EM to determine the structure of another member of the class B family, the calcitonin receptor, in active conformation in complex with salmon calcitonin and its heterotrimeric G protein (3), also emphasizes the relative mobility of ECD and TMD, and the importance of dynamic changes in orientation of these domains. It will be important to gain more insights into the structure and conformational flexibility of apo-receptors in this family to better understand how the natural peptide ligands gain access to the ECD, and to learn more about other possible sites of contact between ECD and TMD that could contribute to conformational changes in the TMD. These reports emphasize the functional importance and likely variations that will exist in the relative orientations of these key structural domains for this class of GPCRs.

[1] Zhang et al. (2017). Structure of the full-length glucagon class B G-protein-coupled receptor. Nature, doi:10.1038/nature222363. [PMID: 28514451]
[2] Siu et al. (2013). Structure of the human glucagon class B G-protein-coupled receptor. Nature, 488:444-449. [PMID: 23863937]
[3] Liang et al. (2017). Phase-plate cryo-EM structure of a class B GPCR-G-protein complex. Nature,doi: 10.1038/nature22327. [Epub ahead of print] [PMID: 28437792]

Comments by Laurence J. Miller (Mayo Clinic, Scottsdale, AZ, USA)

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Hot topics: Crystal structure of GLP-1 receptor transmembrane domain provides insight into allosteric modulation.

The glucagon-like peptide-1 receptor (GLP-1R) is a major target for treatment of Type 2 diabetes but has been refractory to the development of small molecule compounds as potential therapeutics. Song et al., (1) report the first crystal structures of the GLP-1R transmembrane domain in complex with 2 distinct negative allosteric modulators (NAMs) (PF-06372222 and NNC0640). The work provides insight into inactive state structure for the GLP-1R and key interactions that drive inhibitor potency. Moreover, the work allows modelling of an allosteric agonist (and positive allosteric modulator, PAM), Novo Nordisk compound 2, to reveal a potential mechanism for allosteric receptor activation that is supported by mutagenesis and molecular dynamics simulations. The proposed mechanism would lead to a decreased energy barrier for receptor activation through reorganisation of hydrogen bond networks at the base of the receptor that are important for receptor quiescence, and is consistent with the known pharmacology of the PAM in modulating orthosteric peptide activation of the receptor. This work, combined with novel structures of active class B receptors, opens up new possibilities for design of small molecule compounds to manipulate receptor pharmacology and as potential therapeutic drug leads.

[1] Song et al. (2017) Human GLP-1 receptor transmembrane domain structure in complex with allosteric modulators. Nature, doi:10.1038/nature22378. [PMID 28514449]

Comments by Patrick Sexton (Monash Univeristy, Melbourne)

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Guide to IMMUNOPHARMACOLOGY – beta release v1.0, May 2017

We are pleased to announce the first, public, beta-release of the Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb). The GtoImmuPdb is a Wellcome Trust-funded extension to the existing Guide to PHARMACOLOGY (GtoPdb) and the beta-release (v1.0) marks an important milestone in its production and development. GtoImmuPdb aims to provide improved data exchange between immunology and pharmacology expert communities, so to better support research and development of drugs targeted at modulating immune, inflammatory or infectious components of disease. The underlying GtoPdb schema has been extended to incorporate new immune system specific data types (such as processes, cell types and disease) and the GtoPdb website has been developed to surface this new data and incorporate it into the existing search and browse mechanisms. A new Guide to IMMUNOPHARMACOLOGY portal (Figure 1)(www.guidetoimmunopharmacology.org) has been developed, which serves as a unique immunological access-point to the Guide to PHARMACOLOGY.

portal

The GtoImmuPdb enriches the existing GtoPdb by flagging targets and ligands of immunological relevance and linking these targets to immunological process, cell types and relevant diseases. In terms of processes and cell types, GtoImmuPdb has developed top-level categories (Figure 2), that aim to be meaningful and intuitive to immunologists, against which targets and ligands in the database can be annotated. These categories are underpinned by the use of both the Gene Ontology and the Cell Ontology. Using recognised ontologies provides a controlled vocabulary for higher resolution annotation (Figure 3). It also facilitates interoperability between new data types in GtoImmuPdb and external resources that also use these ontologies.

processs_celltype_browse

process_assoc_bcell

Data linking targets and ligands to disease is also incorporated into GtoImmuPdb, with the curation of disease associations using resources such as OrphaNet, Disease Ontology and OMIM (Figure 4).

ligand_v_disease

As well as the development of the GtoImmuPdb Portal, the web-interface has been further developed with immunological data and users in mind. It has been designed to provide a unique ‘GtoImmuPdb view’ of the data, highlighting content of immunological relevance and prioritising immunological data in search results and display. It includes features that highlight targets, target families and ligands of immunological relevance (Figure 5); toggle buttons to enable the GtoImmuPdb view to be switched on and off (Figure 6); and new pages and sections to display immunological data (Figure 7).

Figure2_Harding

 

toggle_target_highlight

 

detailed_view_H1_receptor

Development of the beta-release is ongoing with regular updates planned over the next few months as the quantity of data captured increases and improvements in the site layout and function are made. One of our priorities over the next 6 months is to undertake rigorous site testing with interested user groups to capture more insight and feedback. We welcome those interested and potential future users to get in touch with us.

This project is supported by a 3-year grant awarded to Professor Jamie Davies at the University of Edinburgh by the Wellcome Trust (WT).

Posted in Guide to Immunopharmacology

Database release 2017.4

Our 4th database release of 2017 was published on 23rd May 2017. It now includes 15133 interactions between 2813 targets and 8900 ligands. For full release statistics see the Guide to PHARMACOLOGY About page.

Target Updates

Updates have been made to the following target families:

GPCRs:

LGICs:

The Guide to IMMUNOPHARMACOLOGY

The most major update in this release is the inclusion of the first beta-release of the Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb).
GtoImmuPdb is a Wellcome Trust-funded extension to the existing Guide to PHARMACOLOGY (GtoPdb) and this release marks an important milestone in its production and development. GtoImmuPdb aims to provide improved data exchange between immunology and pharmacology expert communities, so to better support research and development of drugs targeted at modulating immune, inflammatory or infectious components of disease. The underlying GtoPdb schema has been extended to incorporate new immune system specific data types (such as processes, cell types and disease) and the GtoPdb website has been developed to surface this new data and incorporate it into the existing search and browse mechanisms. A new Guide to IMMUNOPHARMACOLOGY portal (www.guidetoimmunopharmacology.org) has been developed, which serves as a unique immunological access-point to the Guide to PHARMACOLOGY.

For more information, please see our separate blog post on the Guide to IMMUNOPHARMACOLOGY beta-release.

Ligand activity graphs

In our 2017.2 release we announced the development of ligand activity graphs which can be used to compare activity ranges across species using data extracted from GtoPdb and ChEMBL.activity_graphs

These have recently been updated to use the latest ChEMBL release (ChEMBL_23), which was made available on 19th May 2017. We have also applied a few minor bug fixes to the graphs, most notably with the box plot display. We are very interested in getting feedback on this new feature and would encourage anyone who has used it or looked at it to get in touch with comments.

Website updates

The latest GtoPdb release has also incorporated changes to our news and hot topics pages. The revised news page has been designed to give greater prominence to our blog feed, which is now our main source of news.

Our hot topics page has also been modified to better capture and present interesting topics in pharmacology. It now presents a more refined list of the latest hot topics, with link from selected ones to our blog, where contributors have provided more detailed and enriched comments.

Posted in Database updates, Guide to Immunopharmacology, Technical

Hot topics: New crystal structure of the full-length Smoothened reveals ligand-dependent interaction between extracellular CRD and the 7TM core of the receptor

Molecular details of receptor activation remain scarce when it comes to Class Frizzled receptors and even less is known about the dynamics between the N-terminal cysteine rich domain (CRD) and the transmembrane domain (TMD) in the absence and presence of ligand. The Class Frizzled comprises 10 isoforms of FZDs (FZD1-10) and Smoothened (SMO), which mediate WNT and Hedgehog signalling respectively. The recently published structure of a full-length SMO bound to the stabilizing compound TC114 builds on emerging concepts from earlier crystal structures of SMO and provides novel insight into how structural rearrangements of the CRD relative to the receptor core coordinate receptor activation while relating this to WNT receptors (1). The ligand-dependent communication between the CRD and the TMD is of special interest because of the known requirement of Class Frizzled receptors to bind endogenous agonists with their CRD. The observed movement of the extracellular extension of SMO-TM6 and extracellular loop 3 suggests a bimodal binding of the agonist to the CRD and the TMD as has been seen for Class B receptors. While this study focuses on the ligand-dependent structural rearrangements on the extracellular part of SMO, it remains unresolved how the conformational changes on the extracellular side of Class Frizzled receptors relate to activating movements of the transmembrane helices on the intracellular side – leaving ample room for future discoveries. The present study opens a new chapter in drug discovery through the use of structure- and mechanism-based drug design to fuel ideas and hopes of successfully targeting FZDs by small molecule drugs. On a more general scale, this work published in Nature Communications by the groups of Fei Xu, Wenfu Tan, Houchao Tao and Raymond Stevens contributes to a better understanding of the role of large extracellular domains in GPCRs with regard to ligand recognition and the engagement of the transmembrane core of the receptor for signal initiation.

[1] Zhang X et al. (2017). Crystal structure of a multi-domain human smoothened receptor in complex with a super stabilizing ligand. Nat Commun., 8:15383. [PMID:28513578].

Comments by Shane C. Wright & Gunnar Schulte (Karolinska Institutet)

Posted in Hot Topics

Hot Topics: Protein-phospholipid interplay revealed with crystals of a calcium pump

Ca2+-ATPases are members of the P-type transporters and are usually regarded as post-stimulus recovery mechanisms, allowing calcium ions to be removed from the cytosol either via re-accumulation into sarcoplasmic/endoplasmic reticulum (the SERCA pumps) or extrusion outside the cell (the PMCA pumps).  Here, Norimatsu and colleagues (1) have used X-ray solvent contrast modulation to assess density maps of four activation states of the SERCA1, focussing on the interaction between the ten transmembrane helices and their surrounding phospholipid environment.  Their observations suggest an unexpected movement of the transporter core, which allows an exaggerated ‘waving’ of the cytoplasmic-extended calcium-binding domain during the cycle of calcium transport.

[1] Norimatsu et al. (2017). Protein-phospholipid interplay revealed with crystals of a calcium pump. Nature 545(7653):193-198. [PMID:28467821]

Comments by Steve Alexander (@mqzspa)

Posted in Hot Topics