Motivation: Recent efforts to computationally identify inhibitors for SARS-CoV-2 proteins have largely ignored the issue of receptor flexibility. We have implemented a computational tool for ensemble docking with the SARS-CoV-2 proteins, including the main protease (Mpro), papain-like protease (PLpro) and RNA-dependent RNA polymerase (RdRp).

Results: Ensembles of other SARS-CoV-2 proteins are being prepared and made available through a user-friendly docking interface. Plausible binding modes between conformations of a selected ensemble and an uploaded ligand are generated by DINC, our parallelized meta-docking tool. Binding modes are scored with three scoring functions, and account for the flexibility of both the ligand and receptor. Additional details on our methods are provided in the supplementary material.

Availability: dinc-covid.kavrakilab.org.

Supplementary Information: Details on methods for ensemble generation and docking are provided as supplementary data online.

Contact: geancarlo.zanatta@ufc.br , kavraki@rice.edu.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836118PMC
http://dx.doi.org/10.1101/2021.01.21.427315DOI Listing

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