GPCRdb in 2021: integrating GPCR sequence, structure and function

By Albert J. Kooistra, Stefan Mordalski, Gáspár Pándy-Szekeres, Mauricio Esguerra, Alibek Mamyrbekov, Christian Munk, György M. Keserü, David E. Gloriam. 2020

298 citations recorded by the source corpus.

Abstract G protein-coupled receptors (GPCRs) form both the largest family of membrane proteins and drug targets, mediating the action of one-third of medicines. The GPCR database, GPCRdb serves >4 000 researchers every month and offers reference data, analysis of own or literature data, experiment design and dissemination of published datasets. Here, we describe new and updated GPCRdb resources with a particular focus on integration of sequence, structure and function. GPCRdb contains all human non-olfactory GPCRs (and >27 000 orthologs), G-proteins and arrestins. It includes over 2 000 drug and in-trial agents and nearly 200 000 ligands with activity and availability data. GPCRdb annotates all published GPCR structures (updated monthly), which are also offered in a refined version (with re-modeled missing/distorted regions and reverted mutations) and provides structure models of all human non-olfactory receptors in inactive, intermediate and active states. Mutagenesis data in the GPCRdb spans natural genetic variants, GPCR-G protein interfaces, ligand sites and thermostabilising mutations. A new sequence signature tool for identification of functional residue determinants has been added and two data driven tools to design ligand site mutations and constructs for structure determination have been updated extending their coverage of receptors and modifications. The GPCRdb is available at https://gpcrdb.org.

Subfields: Cellular and Molecular Neuroscience, Computational Theory and Mathematics, Molecular Biology, Computational Biology & Bioinformatics

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Citations in the corpus

Accurate prediction of protein structures and interactions using a 3-track neural network (2021, neutral): “S7] and that the DeepAccNet model quality predictor ( 12 ) provides a good measure of actual model accuracy (fig.”
AlphaFold2 versus experimental structures: evaluation on G protein-coupled receptors (2022, methodology): “The progress of X-ray-based methods used to be slow [6, 7].”
GPCRdb in 2023: state-specific structure models using AlphaFold2 and new ligand resources (2022, methodology): “Given that this is our fifth publication of a major GPCRdb release (18,19,23,24), and additional resources have published (14,25) after the latest publication (19), we provide an overview of the current data, analysis, data-driven experiment design, and data deposition in Figures 1 and 2.”
Biasing AlphaFold2 to predict GPCRs and kinases with user-defined functional or structural properties (2022, methodology): “By leveraging on the API (Application Programming Interface) of two popular web servers, GPCRdb and KLIFS (Kanev et al., 2021; Kooistra et al., 2021), our script filters templates according to pre-defined structural or functional parameters, allowing for a fully automatic selection of templates with”