Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?
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- dc.contributor.author Kapla, Jon
- dc.contributor.author Rodríguez Espigares, Ismael, 1990-
- dc.contributor.author Ballante, Flavio
- dc.contributor.author Selent, Jana
- dc.contributor.author Carlsson, Jens
- dc.date.accessioned 2021-06-07T07:32:13Z
- dc.date.available 2021-06-07T07:32:13Z
- dc.date.issued 2021
- dc.description.abstract The determination of G protein-coupled receptor (GPCR) structures at atomic resolution has improved understanding of cellular signaling and will accelerate the development of new drug candidates. However, experimental structures still remain unavailable for a majority of the GPCR family. GPCR structures and their interactions with ligands can also be modelled computationally, but such predictions have limited accuracy. In this work, we explored if molecular dynamics (MD) simulations could be used to refine the accuracy of in silico models of receptor-ligand complexes that were submitted to a community-wide assessment of GPCR structure prediction (GPCR Dock). Two simulation protocols were used to refine 30 models of the D3 dopamine receptor (D3R) in complex with an antagonist. Close to 60 μs of simulation time was generated and the resulting MD refined models were compared to a D3R crystal structure. In the MD simulations, the transmembrane helix region of the models generally drifted further away from the crystal structure conformation. However, MD refinement was able to improve the accuracy of the ligand binding mode and the second extracellular loop region. The best refinement protocol improved agreement with the experimentally observed ligand binding mode for a majority of the models. Receptor structures with improved virtual screening performance, which was assessed by molecular docking of ligands and decoys, could also be identified among the MD refined models. Application of weak restraints to the transmembrane helixes in the MD simulations further improved predictions of the ligand binding mode and second extracellular loop. These results provide guidelines for application of MD refinement in prediction of GPCR-ligand complexes and directions for further method development.
- dc.format.mimetype application/pdf
- dc.identifier.citation Kapla J, Rodriguez Espigares I, Ballante F, Selent J, Carlsson J. Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?. PLoS Comput Biol. 2021;17(5):e1008936. DOI: 10.1371/journal.pcbi.1008936
- dc.identifier.doi http://dx.doi.org/10.1371/journal.pcbi.1008936
- dc.identifier.issn 1553-734X
- dc.identifier.uri http://hdl.handle.net/10230/47782
- dc.language.iso eng
- dc.publisher Public Library of Science (PLoS)
- dc.relation.ispartof PLoS Comput Biol. 2021;17(5):e1008936
- dc.rights © 2021 Kapla et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/
- dc.subject.keyword Crystal structure
- dc.subject.keyword G protein coupled receptors
- dc.subject.keyword Simulation and modeling
- dc.subject.keyword Protein structure prediction
- dc.subject.keyword Biochemical simulations
- dc.subject.keyword Protein structure
- dc.subject.keyword Molecular dynamics
- dc.subject.keyword Protein structure determination
- dc.title Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion