Structural features embedded in G protein-coupled receptor co-crystal structures are key to their success in virtual screening

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Structure based drug discovery on GPCRs harness atomic detail X-ray binding pockets and large libraries of potential drug lead candidates in virtual screening (VS) to identify novel lead candidates. Relatively small conformational differences between such binding pockets can be critical to the success of VS. Retrospective VS on GPCR/ligand co-crystal structures revealed stark differences in the ability of different structures to identify known ligands, despite being co-crystallized with the same ligand. When using the OpenEye toolkit and the ICM modeling package, we identify criteria associated with the predictive power of binding pockets in VS that consists of a combination of ligand/receptor interaction pattern and predicted ligand/receptor interaction strength. These findings can guide the selection and refinement of GPCR binding pockets for use in SBDD programs and may also provide a potential framework for evaluating the ability of computational GPCR binding pocket refinement tools in improving the predictive power of binding pockets.

Original languageEnglish
Article numbere0174719
Number of pages29
JournalPLoS ONE
Volume12
Issue number4
DOIs
Publication statusPublished - 1 Apr 2017

Cite this

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abstract = "Structure based drug discovery on GPCRs harness atomic detail X-ray binding pockets and large libraries of potential drug lead candidates in virtual screening (VS) to identify novel lead candidates. Relatively small conformational differences between such binding pockets can be critical to the success of VS. Retrospective VS on GPCR/ligand co-crystal structures revealed stark differences in the ability of different structures to identify known ligands, despite being co-crystallized with the same ligand. When using the OpenEye toolkit and the ICM modeling package, we identify criteria associated with the predictive power of binding pockets in VS that consists of a combination of ligand/receptor interaction pattern and predicted ligand/receptor interaction strength. These findings can guide the selection and refinement of GPCR binding pockets for use in SBDD programs and may also provide a potential framework for evaluating the ability of computational GPCR binding pocket refinement tools in improving the predictive power of binding pockets.",
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Structural features embedded in G protein-coupled receptor co-crystal structures are key to their success in virtual screening. / Coudrat, Thomas; Christopoulos, Arthur; Sexton, Patrick Michael; Wootten, Denise.

In: PLoS ONE, Vol. 12, No. 4, e0174719, 01.04.2017.

Research output: Contribution to journalArticleResearchpeer-review

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