Hot Topics: The atlas of aminergic GPCR mutagenesis

G protein-coupled receptors (GPCRs) are an important family of signal-transducing membrane proteins capable of binding various types of ligands from the extracellular space and activating various signalling pathways inside the cell, rendering them one of the largest protein target families in pharmaceutical research [1]. Receptors of the aminergic GPCRs family are particularly rewarding drug targets as they are implicated in various disease areas, and structure-based drug design has enabled the understanding of ligand binding and function, and the development of more than 500 approved drugs targeting these receptors. Advances in structural biology allowed the determination of more than 300 crystal structures of more than 60 GPCR subtypes to date [2], however, these still represent only a small fraction of known receptor-ligand associations [3].

Site-directed mutagenesis (SDM) is a versatile and frequently employed tool in pharmacological investigations used to infer structural features of protein-ligand interactions [4]. Mutation studies complement structural information provided by crystal structures by defining the roles and relative importance of residues involved in binding, functional activity, and selectivity for ligand chemotypes which have not yet been co-crystallized with their receptors. Community-wide GPCR structure modelling challenges have shown that the best models could be constructed by careful incorporation of mutation and SAR data relating to ligand binding [5]. However, an integrated analysis of receptor and ligand structures and SAR, mutation data, and binding mode prediction has been so far lacking.

The study of Vass et al. can be regarded as a meta-analysis of the site-directed mutagenesis literature for aminergic G protein-coupled receptors [6]. Through an exhaustive database and literature search, the researchers from VU University Amsterdam, Polish Academy of Sciences, University of Copenhagen and Sosei Heptares have collected 6692 mutational data points for 34 aminergic GPCR subtypes of 8 species from 302 publications, covering the chemical space of 540 unique ligands from mutagenesis experiments. This large body of mutation data was also annotated with the structure-based GPCR residue numbering enabling a comparison of mutation effects across different GPCR subtypes and sub-families, and mapped onto the residue positions in the available aminergic crystal structures. Mutation effects were binned into four categories: increased effect, no effect, decreased, and abolished effect, and the data is presented in large overview tables for the five aminergic sub-families. For ligands which had not yet been co-crystallized with their respective receptors, the authors provide predicted binding modes using a combined docking and interaction fingerprint approach to rationalize the mutation effects in light of the ligand SAR.

For each receptor sub-family, a discussion of the known structural receptor-ligand interactions, the ligand chemical space, the structural determinants of receptor-ligand interactions from mutation studies in the amine, major, minor pockets, and the extracellular vestibule, and the possibility of mutation effect extrapolation is provided. The authors also discuss mutation effects of the same ligands across different receptors providing insights into the receptor specific determinants of ligand binding. Finally, an overview is provided of some applications, and the possibilities and limitations of using mutation data to guide the design of novel aminergic receptor ligands.

The authors have deposited the data on Zenodo and in the GPCRdb, and a KNIME workflow was also provided using the 3D-e-Chem KNIME nodes to ease further analysis of the data by the readers [7].

Comments by Chris De Graaf (@Chris_de_Graaf), Director Computation Chemistry, Sosei Heptares.

(1) Santos et al. (2017). A comprehensive map of molecular drug targets. Nat Rev Drug Discov. doi: 10.1038/nrd.2016.230. [PMIDs: 27910877]

(2) Munk et al. (2019). An online resource for GPCR structure determination and analysis. Nat Methods. doi: 10.1038/s41592-018-0302-x. [PMIDs: 30664776]

(3) Vass et al. (2018). Chemical Diversity in the G Protein-Coupled Receptor Superfamily. Trends Pharmacol Sci. doi: 10.1016/ [PMIDs: 29576399]

(4) a) Munk et al. (2016). Integrating structural and mutagenesis data to elucidate GPCR ligand binding. Curr Opin Pharmacol. doi: 10.1016/j.coph.2016.07.003. [PMIDs: 27475047] b) Arimont et al. (2017) Structural Analysis of Chemokine Receptor–Ligand Interactions. J Med Chem doi: 10.1021/acs.jmedchem.6b0130. [PMIDs: 28165741]. c) Jespers et al. (2018). Structural Mapping of Adenosine Receptor Mutations: Ligand Binding and Signaling Mechanisms. Trends Pharmacol Sci. doi: 10.1016/ [PMIDs: 29203139]

(5) a) Kufareva et al. (2011) Status of GPCR modeling and docking as reflected by community-wide GPCR Dock 2010 assessment. Structure. doi: 10.1016/j.str.2011.05.012. [PMIDs: 21827947]; b) Kufareva et al. (2014). Advances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: meeting new challenges. Structure. doi: 10.1016/j.str.2014.06.012. [PMIDs: 25066135]

(6) Vass et al. (2019). Aminergic GPCR-Ligand Interactions: A Chemical and Structural Map of Receptor Mutation Data. J Med Chem. doi: 10.1021/acs.jmedchem.8b00836. [PMIDs: 30351004]

(7) (a); (b)

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