Hot topics: Synthesis and SAR for depsipeptide natural products as selective G protein inhibitors

A team including the Gloriam Group at the University of Copenhagen (also the home of GPCRDB) have paper out in Nature Chemistry reporting the first total synthesis of YM-254890 and FR900359 [1] . These are related cyclic depsipeptide natural products that specifically and potently inhibit the Gq subfamily of G proteins, a relatively rare but useful and pharmacological property [3]. By a combination of solution and solid-phase approaches the team generated sufficient YM-254890 and FR900359 material for confirmation of the structures , pharmacological characterisation and the synthesis of ten new analogues of YM-254890 for SAR analysis. The paper also includes docking studies based on the X-ray crystal structure of YM-254890 in PDB 3AH8 [3]

[1] Xiong et al. (2016). Total synthesis and structure–activity relationship studies of a series of selective G protein inhibitors. Nat Chem, advance online publication, doi:10.1038/nchem.2577

[2] Schrage R, (2015) The experimental power of FR900359 to study Gq-regulated biological processes. Nat Commun. 14;6:10156. doi: 10.1038/ncomms10156, PMID 26658454

[3] Nishimura A. et. al.(2010) Structural basis for the specific inhibition of heterotrimeric Gq protein by a small molecule. Proc Natl Acad Sci; 107(31): 13666–13671. doi: 10.1073/pnas.1003553107, PMID 20639466

The two key potent ligands from the paper are included in the new GtoPdb release 2016.4. Details of this particular curation exercise are given in this blog post.



Comments by Chris Southan

Posted in Hot Topics

Hot topics: X-ray structure of P2X3 receptor

Extracellular ATP is able to activate two families of cell-surface receptors, one of which is the ligand-gated ion channel family of P2X receptors. This family of cation channels is distinct from the remainder of the ligand-gated ion channels, as they are constructed of three (usually homomeric) subunits each with two transmembrane domains. Amongst the P2X receptors, the P2X3 is associated particularly with synaptic transmission in the sensory system and has, therefore, attracted a lot of attention as a potential target for novel analgesics and/or bladder dysfunction therapies.

In this report [1], multiple crystal structures of the P2X3 receptor are described, which allow a novel insight into the gating of a ligand-gated ion channel during the rest-agonist activated-refractory cycle, as well as with antagonist bound.

[1] Mansoor et al. (2016). X-ray structures define human P2X3 receptor gating cycle and antagonist action. Nature 538:66-71. doi: 10.1038/nature19367. [PMID 27626375].

Comments by Steve Alexander


Posted in Hot Topics

GtoPdb database release 2016.4

We are pleased to announce our fourth database release of 2016. Version 2016.4 was published on 13th October 2016. The database is available through the Guide to Pharmacology website, download pages and web-services.

Target updates:

Website updates

A new dendrogram visualisation of VGICs is included on the ion channel page ( It shows a representation of the amino acid sequence relations of the minimal pore regions of the voltage-gated ion channel superfamily. the visualisation was taken from:

The VGL-Chanome: A Protein Superfamily Specialized for Electrical Signaling and Ionic Homeostasis. Frank H. Yu and William A. Catterall. Sci STKE. 2004 Oct 5;2004(253):re15. PMID: 15467096. DOI: 10.1126/stke.2532004re15


We have created a new sister database to the main Guide to PHARMACOLOGY – SynPharm, a database of drug-responsive protein sequences. The sequences in SynPharm are derived from interactions from the Guide to PHARMACOLOGY and using data from the Protein Data Bank. It is expected that the SynPharm database will grow as the principle Guide to PHARMACOLOGY database is updated – or indeed as further structural data is added to the PDB database pertaining to interactions already documented.

Please read the introductory SynPharm blog post (4th October 2016).

A summary of the current data can be found at

Database Statistics

In total the database now contains 14,701curated interactions across 2,794 human targets and 8,674 ligands. More specifically, the database contain 1,465 human targets that have quantitative interactions to a ligand.


Number of human targets in GtoPdb 2016.4. Measured by number of distinct UniProt entries includes for a given target class


Breakdown of ligand classes in GtoPdb 2016.4

Posted in Database updates

Why Data Citation Is a Computational Problem


By Peter Buneman

The database development team encouraged me to write this off-topic blog on data citation, as it may be of interest to people involved with the IUPHAR/BPS Guide to Pharmacology (GtoPdb).

It must be almost ten years ago that Tony Harmar mentioned that he was thinking of buying digital object identifiers for the then IUPHAR database. It turned out that he was hoping that this would confer some scholarly recognition to the database, but what he really wanted to do was to get people to cite it, just as they would cite any other publication. Among other things, he wanted to ensure that the relevant contributors and curators received proper credit.

I thought about the problem for a while, wrote a rather naive paper about it, and more or less forgot about it for a few years. Then data citation became a hot topic, and with some colleagues started to think about it again. Here’s a problem: GtoPdb does a passable job of specifying the citation for each page that you see in the Web presentation, but what citation would you provide for some arbitrary SQL query on the underlying data? It turns out that this is a ubiquitous problem in data citation, and one that is tricky to solve in general.

My colleagues Susan Davidson, James Frew and I produced a general approach to this and sent it to Communications of the ACM — a publication that is widely read by computer scientists. They liked it to the extent that they made it a cover story and produced a film about it.

So thanks to Tony for the idea and thanks to the curators of GtoPdb for letting us use their database as a guinea pig.

Follow this link to the full CACM article, Why Data Curation Is A Computational Problem.

Follow this link to the video,

Posted in Uncategorized

SynPharm: A New Annexe to the Guide to PHARMACOLOGY

We have created a new sister database to the main Guide to PHARMACOLOGY (GtoPdb) – SynPharm, a database of drug-responsive protein sequences.

Each sequence in SynPharm is derived from a GtoPdb interaction. In each case we have identified the continuous protein sequence within the receptor chain that facilitates that interaction, and provided structural, visual, spatial and affinity data.

SynPharm ligand receptor complex

A peptide ligand (R-spondin-1) bound to its receptor (LGR4), with the bind sequence highlighted in green. See its page for more details.

Bind Sequences

Each sequence in the database represents a potentially ligand responsive protein sequence. In addition to providing a pharmacological reference as to the portion of protein chains which actually mediate their interactions with drugs, it is also hoped that SynPharm could act as a library of transferable protein modules to synthetic biologists, enabling the drug responsiveness to be conferred to a protein of choice.

In order to allow researches to assess the likelihood that a bind sequence (as the drug responsive elements are termed) will function in isolation, certain metrics are provided. We provide a ‘contact ratio’ – the ratio of internal contacts (all non-hydrogen atom pairs within the sequence within 5 Angstroms of each other, excluding atoms within two covalent bonds of each other) and external contacts (all non-hydrogen atom pairs between the sequence and the rest of the chain, less than 5 Angstroms) – and a distance matrix to show the ‘globularity’ of the sequences. Each sequence also contains a manipulable 3D  visualisation of the sequence in question.


A example of a residue distance matrix. The bind sequence is represented by a dotted black line within the context of the protein chain it derives from.

In addition, we provide pages for each of the ligands that interact with a sequence, along with a small selection of the data on the ligand from the main Guide to PHARMACOLOGY database.

Creating the Data

Each interaction in the Guide to PHARMACOLOGY was mapped to one or more PDB files where possible. Some already had PDB information, and where this was not the case, the RCSB web services were queried by SMILES, InChI, name and peptide sequence (in the case of ligands) and accession number (in the case of targets) to identify more. In total, 704 interactions mapped to at least one PDB code, and after manually removing some false maps, this came down to 672. Though a relatively small proportion of the 15,000 or so interactions that GtoPdb contains, it is merely an indicator that most interactions observed have do not yet have high quality structural data.

Each interaction-PDB map was turned into a sequence by first identifying the HET code and ID of the ligand within that PDB file (generally provided by the PDB REMARK records), then identifying the residues that facilitate binding (again most PDB files already annotate this but in cases where this is not true, atomic distances were used to identify probable residues), and then using these to construct a continuous sequences. Not all maps were suitable to this – some had binding sites split across multiple protein chains, and yet more contained too many missing residues – residues flagged as missing from the crystallographic (or otherwise) experiment from which the PDB was derived. Ultimately 540 interactions had at least one PDB map that could be used to create a sequence.

It is expected that the SynPharm database will grow as the principle Guide to PHARMACOLOGY database is updated – or indeed as further structural data is added to the PDB database pertaining to interactions already documented.

A summary of the current data can be found at

Posted in Uncategorized

GtoImmuPdb: technical update September 2016


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).


Figure 1: Links to process and cell type association lists pages from GtoImmuPdb portal (

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.


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.


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).


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