GPCRdb in 2021: integrating GPCR sequence, structure and function

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.

Figure 1.

Overview of GPCRdb resources. For data (top), the numbers listed first are the current number of entries and those in parenthesis are for the previous GPCRdb update published in Nucleic Acids Research (23). A range of analysis and visualization tools (mid) allow for generation of new results and figures for publication or presentation. Data driven tools (bottom mid-right) can help to design new experiments. *The number of structure models decreases, and the number of refined structures increases as more receptors and their states (inactive, intermediate and active) are covered by experimental structures (see the Structures and Structure models sections).

Figure 2.

Sequence signature tool to identify residue positions that are functional determinants. (A) Simplified visualization of the sequence signature tool pipeline. Structure based alignments of the two receptors sets are compared to find each residue position's property with the maximum conservation difference for which the user defines a cutoff. (B) Results from a sequence signature analysis of aminergic receptor that bind ergotamine strongly (K_i <10 nM) or not at all (K_i >5000 nM) (31) and a percent property conservation difference cutoff set to 50%. This shows the sequence signature (top), structure-based sequence alignments of the two input sequence sets (mid) and an alternative numeric signature implementing z-scale amino acid descriptors (bottom, see Materials and Methods). Residue property details can be viewed by clicking on the (+) button. (C) Phylogenetic tree of the receptors used in the case study and residue positions of the amino acids interacting with Ergotamine. (D) Mapping of the ergotamine selectivity determinant positions (receptor sets 1 and 2 in green and orange Cα spheres, respectively) identified by the sequence signature tool onto a serotonin 5-HT_2C receptor structure (31).