ArticleACS chemical neuroscience2020
Binding Characterization of GPCRs-Modulator by Molecular Complex Characterizing System (MCCS).
Article in ACS chemical neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Exploring Trop-2-Nanobody PPI Interactions through Molecular Dynamics Simulations and Biovalidations.ACS omega · 2026Article
- Computational approaches to druggable site identification: Current status and future perspective.Acta pharmaceutica Sinica. B · 2026Review
- Metabolism-guided development of Ko143 analogs as ABCG2 inhibitors.European journal of medicinal chemistry · 2023Article
- Elucidation of Binding Features and Dissociation Pathways of Inhibitors and Modulators in SARS-CoV-2 Main Protease by Multiple Molecular Dynamics Simulations.Molecules (Basel, Switzerland) · 2022Article
- How Do Modulators Affect the Orthosteric and Allosteric Binding Pockets?ACS chemical neuroscience · 2022Article
- In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators.Molecules (Basel, Switzerland) · 2022Article
- SYNBIP: synthetic binding proteins for research, diagnosis and therapy.Nucleic acids research · 2022Article
- Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design.Pharmaceuticals (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Increasing attention has been devoted to allosteric modulators as the preferred therapeutic agents for their colossal advantages such as higher selectivity, fewer side effects, and lower toxicity since they bind at allosteric sites that are topographically distinct from the classic orthosteric sites. However, the allosteric binding pockets are not conserved and there are no cogent methods to comprehensively characterize the features of allosteric sites with the binding of modulators. To overcome this limitation, our lab has developed a novel algorithm that can quantitatively characterize the receptor-ligand binding feature named Molecular Complex Characterizing System (MCCS). To illustrate the methodology and application of MCCS, we take G protein coupled receptors (GPCRs) as an example. First, we summarized and analyzed the reported allosteric binding pockets of class A GPCRs using MCCS. Sequentially, a systematic study was conducted between cannabinoid receptor type 1 (CB1) and its allosteric modulators, where we used MCCS to analyze the residue energy contribution and the interaction pattern. Finally, we validated the predicted allosteric binding site in CB2 via MCCS in combination with molecular dynamics (MD) simulation. Our results demonstrate that the MCCS program is advantageous in recapitulating the allosteric regulation pattern of class A GPCRs of the reported pockets as well as in predicting potential allosteric binding pockets. This MCCS program can serve as a valuable tool for the discovery of small-molecule allosteric modulators for class A GPCRs.
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