GtoImmuPdb: technical update September 2016

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The focus of development in the last month has been on preparing the GtoImmuPdb portal for alpha-release and building landing-pages for process and cell type association lists.

An early synopsis of the project can be found in this blog post. Previous technical blogs are available for February, May & August 2016.

Development Progress

List pages for process and cell type associations

We have developed landing pages that are reached when clicking on any of the main process or cell type categories in either of the process or cell type panel on the GtoImmuPdb portal (see Figure 1).

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Figure 1: Links to process and cell type association lists pages from GtoImmuPdb portal (www.guidetopharmacology.org/immuno)

These pages list the protein targets in the database that are associated with either immunological processes or immune system cell types. In each case, the pages are split, using tabs, to show targets associated with each of the main process or cell type categories. The targets in each list are then separated by their target-class (e.g. GPCRs, ion channel, enzymes etc.). An example of the immuno process association list page is shown in figure 2.

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Figure 2: GtoImmuPdb process association list page. Showing targets associated with the ‘proliferation and cell death’ category.

The table for the process associations gives the target name and family, any process association comments and lists Gene Ontology (GO) terms annotated to the target (with ID and evidence code). Two further columns show if the target has been specifically tagged as being in the Guide to IMMUNOPHARMACOLOGY by our curators, with any associated comments.

It is worth a reminder here that we auto-populate the GO annotations from UniProt. Therefore, we will see targets appearing under the process associations that have not been directly curated into GtoImmuPdb by our curators. For the time-being we will continue with the distinction between targets associated to processes (via GO only) and those that our curatorial team have identified as being of immunological relevance, and therefore directly curated as being ‘in GtoImmuPdb’.

The table for the cell type associations (see figure 3) gives the same colums as for process associations. With the exception that it lists Cell Ontology terms with their IDs.

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Figure 3: GtoImmuPdb cell type association list page

Other Developments

Work has continued on implementing the site search to incorporate all new columns for process and cell type associations. This includes top-level category names, GO and Cell Ontology terms & definitions and all association comments.

A few fixes have been made to out submission tool to better handle cell type association input.

Portal development

A new logo has been added to the Guide to IMMUNOPHARMACOLOGY portal. A bespoke design by Dr. Adam Pawson. The menu bar has been adjusted to include a link to the GtoPdb home page. We have also modified some of the links within the menu-bar to keep the GtoImmuPdb focus (for target links).

Alpha-release

Our plan is to release the first alpha-version of the Guide to IMMUNOPHARMACOLOGY at the beginning of October.

This will be an internal release on our development site and will be accompanied by detailed release notes and a user guide to navigating the new pages.

 

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: High resolution structure of the voltage-gated skeletal muscle Ca2+ channel complex

In a recent article in Nature [1], Wu et al. present the cryo-electron microscopy structure of the rabbit Cav1.1 complex at a nominal resolution of 3.6 Å. Enrichment of purified channel particles without carbon film increased resolution and allowed to delineate structural features of the channel beyond those published by the authors in Science [2] six months earlier. The new structure reveals the channel in a (most likely) inactivated state (pore closed, voltage-sensors “up”), provides more complete structural detail of the α2δ-subunit and its interaction with extracellular surface of the pore-forming α1-subunit and unveils formation of a globular domain by direct interaction of the proximal C-terminal tail of α1 with its intracellular III-IV linker.
The new structural information provides new perspectives to address long-standing open questions. It will help to model human disease-related missense mutations within the Cav1.1 α1-subunit structure revealing the molecular mechanisms causing aberrant channel function, such as the formation of omega-pores in hypokalemic periodic paralysis [3]. The drug binding domains for Ca2+ channel blockers, widely used as antihypertensive drugs by blocking highly homologous Cav1.2 L-type channels in arterial resistance vessels, are highly conserved in Cav1.1. Together with recently published high resolution structure of the receptor sites for these drugs within the Ca2+-selective bacterial Na+-channel (NavAb) derivative CavAb [4], the new Cav1.1 structure will now allow to further refine the molecular details of drug interactions with L-type Ca2+ channels. The unexpected finding of a globular domain formed by the proximal C-terminus and the cytoplasmic III-IV linker of the pore subunit could provide the structural missing link for understanding how the C-terminus mediates protein kinase A regulation of the channel and controls voltage- and Ca2+-dependent channel gating in Cav1.1 and other voltage-gated Ca2+ channels.
Finally, it will be interesting to see how well the Cav1.1 α1-subunit structure was predicted by homology modeling using bacterial Na+-channels (like NavAb) or mammalian K+-channels as a template [5].

[1] Wu et al. (2016). Structure of the voltage-gated Ca2+ channel Cav1.1 at 3.6 Å resolution. Nature 537:191-196. [PMID 27580036].

[2] Wu et al. (2015). Structure of the voltage-gated calcium channel Cav1.1 complex. Science 350: aad2395. [PMID 26680202].

[3] Wu et al. (2012). A calcium channel mutant mouse model of hypokalemic periodic paralysis. J. Clin. Invest. 122: 4580–4591. [PMID 23187123].

[4] Tang et al. (2016). Structural basis for inhibition of a voltage-gated Ca(2+) channel by Ca(2+) antagonist drugs. Nature 537: 117–121. [PMID 27556947].

[5] Tuluc et al. (2016). Molecular interactions in the voltage sensor controlling gating properties of Cav calcium channels. Structure 24:261–271. [PMID 26749449].

Comments by Jörg Striessnig (Department of Pharmacology and Toxicology – Institute of Pharmacy, Universität Innsbruck)

Posted in Hot Topics

Hot topics: Allosteric Modulation of Receptor Function and Regulation

Changeux and Christopoulos have recently described in Cell [1] how common mechanisms link the allosteric sites of activation and response within the four major receptor families of ligand- and voltage-gated ion channels, G-protein-coupled receptors, nuclear hormone receptors, and receptor tyrosine kinases. As stated in the classical “Monod-Wyman-Changeux” model [2], the signal transduction mechanism operates through the selective stabilization of the particular state to which any ligand preferentially binds. Recent research shows that these states are affected by multiple factors including oligomerization, distinct conformational ensembles, intrinsically disordered regions, and allosteric modulatory sites. These processes can be perturbed by mutations that shift the equilibrium of receptor functional states and lead to disease [3]. Conversely, marketed medicines now include a large number of allosteric modulators with the advantages of fine-tune physiological responses and offer higher on-target selectivity via more diverse binding sites [4]. Such modulators can also display increased functional selectivity through biased agonism (i.e. the association with a distinct receptor conformation and signal routing). This review summarises the unifying mechanisms for the allosteric modulation of receptor classes and provides a clear demonstration of the associated pharmacological targeting opportunities.

[1] Changeux, J.-P. and A. Christopoulos (2016). Allosteric Modulation as a Unifying Mechanism for Receptor Function and Regulation. Cell. 166(5): p. 1084-1102. [PMID: 27565340]

[2] Monod, J., J. Wyman, and J.P. Changeux (1965). On the nature of allosteric transitions: a plausible model. J. Mol. Biol. 12: p.88-118. [PMID: 14343300]

[3] Changeux, J.-P. (2013). 50 years of allosteric interactions: the twists and turns of the models. Nat. Rev. Mol. Cell Biol. 14(12): p.819-29. [PMID: 24150612]

[4] Gentry, P.R., P.M. Sexton, and A. Christopoulos (2015). Novel Allosteric Modulators of G Protein-coupled Receptors. Journal of Biological Chemistry. 290(32): p.19478-19488. [PMID: 26100627]

Comments by David E. Gloriam (Department of Drug Design and Pharmacology, University of Copenhagen).

 

Posted in Hot Topics

Hot topics: Analysis of protein-coding genetic variation in humans

Lek et al. [1] in Nature, describes a tour de force large scale reference data set of high-quality protein-coding variation generated via the Exome Aggregation Consortium (ExAC) [2]. This covers 7,404,909  variants of different types that can be interrogated from an open browser set up by the team http://exac.broadinstitute.org/  [2]. Many interesting and important aspects of protein variation in both medical and evolutionary contexts are subject to statistical analysis and the results discussed. This includes loss-of function (LoF) with both clinical manifestations and consequent possible opportunities for pharmacological intervention. As just one example they investigate genetic intolerance to 179,774 high-confidence protein truncation variants (PTVd) that mapped to 3,230 highly LoF-intolerant genes. It turns out that 72% have no human disease phenotype in the OMIM or ClinVar databases. The Exac resource provides opportunities for detailed analysis of  functional variation as well as a filter for analysis of candidate pathogenic variants in Mendelian diseases. The paper also indicates that most of the proposed burden of Mendelian disease alleles per-person highlighted in previous reports, is due to misclassification in the literature and/or in databases [3]. In curating target records for GtoPdb the team have been finding it increasingly challenging to select between the many sources of protein variation and different levels of supporting evidence for the phenotypic consequences thereof. On the basis of these papers and our initial assessment of their database, we would now recommend Exac as a first-stop-shop for browsing the genomic variation landscape of GtoPdb targets, with GPCRdb, Swiss-Var, ClinVar and Orphanet as orthogonal backup.

[1] Lek et al. (2016). Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291. [PMID: 27535533]

[2] Karczewski et al. (2016) The ExAC Browser: Displaying reference data information from over 60,000 exomes. bioRxiv (19 August 2016), 070581, doi:10.1101/070581 

[3] Walsh et al. (2016). Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples.
Genetics in Medicine. Aug 17. doi: 10.1038/gim.2016.90. [Epub ahead of print]. [PMID: 27532257]

Comments by Chris Southan

Posted in Hot Topics

Hot Topics: Discovery of opioid analgesics with reduced side effects

Manglik et al. [1] , writing in Nature, believe they may have found a new form of painkiller that works just as well as morphine but lacks its potentially lethal side effect. The authors have found it is not addictive by discovering a biased agonist that selectively targets the G-protein pathway over β-arrestin. Binding of agonists, such as morphine, to the μ-opioid-receptor cause very powerful reductions in the sensation of pain or analgesia via the G-protein signalling pathway but has the major side-effect of respiratory depression (the major cause of death in heroin addicts) and constipation. A further unwanted side effect limiting the use of morphine is addiction by activating the dopaminergic reward circuits. The authors show the new  μ-opioid agonist PZM21 selectively activates the G-protein signalling pathway to give the desired analgesia in animal models but does not activate β-arrestin pathway, so causes little respiratory depression or constipation nor alters the dopamine pathway so would be predicted not to be addictive.

The research is important as the authors report PZM21 in mice was comparable to morphine but longer lasting. Interestingly PZM21 reduced pain in the CNS but not spinal cord in mouse models.

A biased opioid agonist TRV130 is now in Phase III trials by the company Trevena Inc that is structurally unrelated to PZM21 but has a similar pharmacological profile. Taken together, the two compounds suggest that agonists biased to the Gi/o-pathway (rather than possible differences in other pharmacological properties such as pharmacokinetics)  represent a new strategy for pain control.

[1] Manglik A. et al. (2016). Structure-based discovery of opioid analgesics with reduced side effects. Nature. doi:10.1038/nature19112 advance online publication: 1-6.

Comments by Anthony Davenport

n.b. the  two relevant ligands curated into GtoPdb are show below. As a new entry 9286 PZM21 will go live in release 2106.4 (September) but TRV130 was already captured as ligand 7334

Capture

 

Posted in Hot Topics

GtoImmuPdb: technical update August 2016

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Since our last update in May 2016 the major development extension to the Guide to Immunopharmacology (GtoImmuPdb) has been to incorporate cell type associations and develop the web-application code to display both process and cell type data.

As a reminder, a early synopsis of the project can be found in this blog post and earlier technical updates from February and May.

Development Progress

Cell Type Associations

Previously, we had written a parser to capture and populate cell type data from the Cell Ontology into the database. Since then we have determined a set of 7 high-level, immuno-relevant cell type classes (or categories), against which targets in GtoImmuPdb will be annotated. The 7 classes are as follows:

1: pro-B-lymphocytes, B lymphocytes & Plasma cells [B lymphcytes]
lymphocyte of B lineage CL:0000945
2: T lymphocytes (alpha-beta type) and their immediate progenitors [T lymphocytes (alpha-beta)]
alpha-beta T cell CL:0000789
3: T lymphocytes (gamma-delta type) and their immediate progenitors [T lymphocytes (gamma-delta)]
gamma-delta T cell CL:0000798
4: Natural Killer (NK) cells [NK cells]
natural killer cell CL:0000623
5: Polymorphonuclear leukocytes (neutrophils, eosinophils, basophils) [Polymorphonuclear leukocytes] [Granulocytes]
granulocyte CL:0000094
6: Mononuclear leukocytes (syn: monocytes) (macrophages, dendritic cells, Kupffer cells) [Mononuclear leukocytes]
monocyte CL:0000576
macrophage CL:0000235
dendritic cell CL:0000451
7: Mast cells
mast cell CL:0000097

We have assigned one or more Cell Ontology parent terms to each class. Curators will be able to annotate targets with any child terms of those parents when adding/editing cell type associations. There is also provision for free text comments about the association and the ability to include any references.

Submission Tool

The submission tool has been extended to enable the capture of cell type-target associations and related data. It has also been modified to better capture data relating to process associations (namely to include references).

GtoImmuPdb Portal

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Cell type associations form in submission tool

We have continued work on the alpha-version of the GtoImmuPdb portal, and extensions to the main GtoPdb web-application to incorporate and surface GtoImmuPdb data. Previously we had implemented a toggle on target family pages to highlight targets of relevance to GtoImmuPdb. The idea behind this is so that whichever route a user takes to get to a list of targets or target families – the immuno-view can be easily switch on or off.

We have also extended the detailed target pages to display immunopharmacology comments (specific to the target), cell type associations and process associations.

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Cell type and process association data being surface on the detailed target pages.

The layout of the cell type associations contains one section per each high-level cell type class. Within each section all Cell Ontology terms that have been annotated against the target are displayed, alongside comments and references.

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Close-up of Immuno Cell Type Associations section of detailed target page

Similarly, the layout of the process associations has one section per high-level process class, which includes comments and references. it also includes a list of Gene Ontology (GO) Processes that are annotated to the target. These GO annotations are not input by our curators, but picked up from GO and UniProt (auto-curated). We are including the GO evidence code for these annotations.

Please note, all web-app development is only available on our restricted access test site.

Our next steps will be to improve the layout of these sections – potentially collapsing the list of GO and Cell Ontology terms (in some cases the number of terms annotated to a target can be quite high).
We will also be working on extending the code that handles our site search to include all aspects of cell type associations.
We anticipate the full alpha-release to be made in late September/early October 2016.

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

GtoPdb database release 2016.3

We are pleased to announce our third database release of 2016. Version 2016.3 was published on 21st July 2016. The database is available through the Guide to Pharmacology website, download pages and web-services. In this release, our curators have added comments to all approved drugs in the database (1,290). These comments are included in the ligand details we submit to PubChem.

Target updates:

Website updates

A short, introductory video of the Concise Guide to Pharmacology has been added to the homepage. We will be bringing you more news about the concise guide through this blog in the future – so look out for those. The first, and introduction to the Concise Guide can be found here.

We have also made some minor modifications to our news, updates and announcements, consolidating these in this blog so that there is a single new feed.

Database Statistics

In total the database now contains 14,577 curated interactions across 2,789 human targets and 8,611 ligands. More specifically, the database contain 1,429 human targets that have quantitative interactions to a ligand.

human_targets

Number of human targets in GtoPdb 2016.3. Measured by number of distinct UniProt entries includes for a given target class

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Breakdown of ligand classes in GtoPdb 2016.3

View all the latest database content stats here.

Posted in Database updates