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- W2769643022 endingPage "e1005819" @default.
- W2769643022 startingPage "e1005819" @default.
- W2769643022 abstract "G protein-coupled receptors (GPCRs) play crucial roles in cell physiology and pathophysiology. There is increasing interest in using structural information for virtual screening (VS) of libraries and for structure-based drug design to identify novel agonist or antagonist leads. However, the sparse availability of experimentally determined GPCR/ligand complex structures with diverse ligands impedes the application of structure-based drug design (SBDD) programs directed to identifying new molecules with a select pharmacology. In this study, we apply ligand-directed modeling (LDM) to available GPCR X-ray structures to improve VS performance and selectivity towards molecules of specific pharmacological profile. The described method refines a GPCR binding pocket conformation using a single known ligand for that GPCR. The LDM method is a computationally efficient, iterative workflow consisting of protein sampling and ligand docking. We developed an extensive benchmark comparing LDM-refined binding pockets to GPCR X-ray crystal structures across seven different GPCRs bound to a range of ligands of different chemotypes and pharmacological profiles. LDM-refined models showed improvement in VS performance over origin X-ray crystal structures in 21 out of 24 cases. In all cases, the LDM-refined models had superior performance in enriching for the chemotype of the refinement ligand. This likely contributes to the LDM success in all cases of inhibitor-bound to agonist-bound binding pocket refinement, a key task for GPCR SBDD programs. Indeed, agonist ligands are required for a plethora of GPCRs for therapeutic intervention, however GPCR X-ray structures are mostly restricted to their inactive inhibitor-bound state." @default.
- W2769643022 created "2017-12-04" @default.
- W2769643022 creator A5016689951 @default.
- W2769643022 creator A5037578914 @default.
- W2769643022 creator A5054085362 @default.
- W2769643022 creator A5075463548 @default.
- W2769643022 creator A5078874300 @default.
- W2769643022 date "2017-11-13" @default.
- W2769643022 modified "2023-09-25" @default.
- W2769643022 title "Improving virtual screening of G protein-coupled receptors via ligand-directed modeling" @default.
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- W2769643022 doi "https://doi.org/10.1371/journal.pcbi.1005819" @default.
- W2769643022 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5708846" @default.