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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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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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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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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