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Inspecting the Mechanism of Fragment Hits Binding on SARS-CoV-2 M^pro by Using Supervised Molecular Dynamics (SuMD) Simulations.

ABSTRACT: Computational approaches supporting the early characterization of fragment molecular recognition mechanism represent a valuable complement to more expansive and low-throughput experimental techniques. In this retrospective study, we have investigated the geometric accuracy with which high-throughput supervised molecular dynamics simulations (HT-SuMD) can anticipate the experimental bound state for a set of 23 fragments targeting the SARS-CoV-2 main protease. Despite the encouraging results herein reported, in line with those previously described for other MD-based posing approaches, a high number of incorrect binding modes still complicate HT-SuMD routine application. To overcome this limitation, fragment pose stability has been investigated and integrated as part of our in-silico pipeline, allowing us to prioritize only the more reliable predictions.

SUBMITTER: Bissaro M

PROVIDER: S-EPMC8250706 | biostudies-literature |

REPOSITORIES: biostudies-literature

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