DINC-COVID : a webserver for ensemble docking with flexible SARS-CoV-2 proteins
Hall-Swan, Sarah and Devaurs, Didier and Rigo, Mauricio M. and Antunes, Dinler A. and Kavraki, Lydia E. and Zanatta, Geancarlo (2021) DINC-COVID : a webserver for ensemble docking with flexible SARS-CoV-2 proteins. Computers in Biology and Medicine, 139. 104943. ISSN 1879-0534 (https://doi.org/10.1016/j.compbiomed.2021.104943)
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Abstract
An unprecedented research effort has been undertaken in response to the ongoing COVID-19 pandemic. This has included the determination of hundreds of crystallographic structures of SARS-CoV-2 proteins, and numerous virtual screening projects searching large compound libraries for potential drug inhibitors. Unfortunately, these initiatives have had very limited success in producing effective inhibitors against SARS-CoV-2 proteins. A reason might be an often overlooked factor in these computational efforts: receptor flexibility. To address this issue we have implemented a computational tool for ensemble docking with SARS-CoV-2 proteins. We have extracted representative ensembles of protein conformations from the Protein Data Bank and from in silico molecular dynamics simulations. Twelve pre-computed ensembles of SARS-CoV-2 protein conformations have now been made available for ensemble docking via a user-friendly webserver called DINC-COVID (dinc-covid.kavrakilab.org). We have validated DINC-COVID using data on tested inhibitors of two SARS-CoV-2 proteins, obtaining good correlations between docking-derived binding energies and experimentally-determined binding affinities. Some of the best results have been obtained on a dataset of large ligands resolved via room temperature crystallography, and therefore capturing alternative receptor conformations. In addition, we have shown that the ensembles available in DINC-COVID capture different ranges of receptor flexibility, and that this diversity is useful in finding alternative binding modes of ligands. Overall, our work highlights the importance of accounting for receptor flexibility in docking studies, and provides a platform for the identification of new inhibitors against SARS-CoV-2 proteins.
ORCID iDs
Hall-Swan, Sarah, Devaurs, Didier ORCID: https://orcid.org/0000-0002-3415-9816, Rigo, Mauricio M., Antunes, Dinler A., Kavraki, Lydia E. and Zanatta, Geancarlo;-
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Item type: Article ID code: 90232 Dates: DateEvent1 December 2021Published15 October 2021Published Online11 October 2021AcceptedSubjects: Science > Mathematics > Electronic computers. Computer science
Medicine > Medicine (General)
Science > Microbiology > VirologyDepartment: UNSPECIFIED Depositing user: Pure Administrator Date deposited: 13 Aug 2024 14:53 Last modified: 01 Oct 2024 08:48 URI: https://strathprints.strath.ac.uk/id/eprint/90232