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Exploring the signaling space of a GPCR using bivalent ligands with a rigid oligoproline backbone.

ABSTRACT: G protein-coupled receptors (GPCRs) are one of the most important drug-target classes in pharmaceutical industry. Their diversity in signaling, which can be modulated with drugs, permits the design of more effective and better-tolerated therapeutics. In this work, we have used rigid oligoproline backbones to generate bivalent ligands for the gastrin-releasing peptide receptor (GRPR) with a fixed distance between their recognition motifs. This allows the stabilization of GPCR dimers irrespective of their physiological occurrence and relevance, thus expanding the space for medicinal chemistry. Specifically, we observed that compounds presenting agonists or antagonists at 20- and 30-Å distance induce GRPR dimerization. Furthermore, we found that 1) compounds with two agonists at 20- and 30-Å distance that induce dimer formation show bias toward Gq efficacy, 2) dimers with 20- and 30-Å distance have different potencies toward β-arrestin-1 and β-arrestin-2, and 3) the divalent agonistic ligand with 10-Å distance specifically reduces Gq potency without affecting β-arrestin recruitment, pointing toward an allosteric effect. In summary, we show that rigid oligoproline backbones represent a tool to develop ligands with biased GPCR signaling.

SUBMITTER: Romantini N

PROVIDER: S-EPMC8640787 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Exploring the signaling space of a GPCR using bivalent ligands with a rigid oligoproline backbone.

Romantini Nina N Alam Shahidul S Dobitz Stefanie S Spillmann Martin M De Foresta Martina M Schibli Roger R Schertler Gebhard F X GFX Wennemers Helma H Deupi Xavier X Behe Martin M Berger Philipp P

Proceedings of the National Academy of Sciences of the United States of America 20211101 48

G protein-coupled receptors (GPCRs) are one of the most important drug-target classes in pharmaceutical industry. Their diversity in signaling, which can be modulated with drugs, permits the design of more effective and better-tolerated therapeutics. In this work, we have used rigid oligoproline backbones to generate bivalent ligands for the gastrin-releasing peptide receptor (GRPR) with a fixed distance between their recognition motifs. This allows the stabilization of GPCR dimers irrespective ...[more]

PMID: 34810259

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Project description:The rapid growth of structural information for G-protein-coupled receptors (GPCRs) has led to a greater understanding of their structure, function, selectivity, and ligand binding. Although novel ligands have been identified using methods such as virtual screening, computationally driven lead optimization has been possible only in isolated cases because of challenges associated with predicting binding free energies for related compounds. Here, we provide a systematic characterization of the performance of free-energy perturbation (FEP) calculations to predict relative binding free energies of congeneric ligands binding to GPCR targets using a consistent protocol and no adjustable parameters. Using the FEP+ package, first we validated the protocol, which includes a full lipid bilayer and explicit solvent, by predicting the binding affinity for a total of 45 different ligands across four different GPCRs (adenosine A2AAR, β1 adrenergic, CXCR4 chemokine, and δ opioid receptors). Comparison with experimental binding affinity measurements revealed a highly predictive ranking correlation (average spearman ρ = 0.55) and low root-mean-square error (0.80 kcal/mol). Next, we applied FEP+ in a prospective project, where we predicted the affinity of novel, potent adenosine A2A receptor (A2AR) antagonists. Four novel compounds were synthesized and tested in a radioligand displacement assay, yielding affinity values in the nanomolar range. The affinity of two out of the four novel ligands (plus three previously reported compounds) was correctly predicted (within 1 kcal/mol), including one compound with approximately a tenfold increase in affinity compared to the starting compound. Detailed analyses of the simulations underlying the predictions provided insights into the structural basis for the two cases where the affinity was overpredicted. Taken together, these results establish a protocol for systematically applying FEP+ to GPCRs and provide guidelines for identifying potent molecules in drug discovery lead optimization projects.

Dataset Information

Exploring the signaling space of a GPCR using bivalent ligands with a rigid oligoproline backbone.

Publications

Exploring the signaling space of a GPCR using bivalent ligands with a rigid oligoproline backbone.

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