Computational Prediction of the Potential Target of SARS-CoV-2 Inhibitor Plitidepsin via Molecular Docking, Dynamic Simulations and MM-PBSA Calculations.

ABSTRACT: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication depends on the interaction between the viral proteins and the human translation machinery. The cytotoxic peptide plitidepsin was found to inhibit CoV-2 up to 90 % at a concentration of 0.88 nM. In vitro studies suggest that this activity may be attributed to the inhibition of the eukaryotic translation elongation factor 1A (eEF1A). However, recent reports raised the potential for other cellular targets which plitidepsin may use to exert its potent antiviral activity. The lack of data about these potential targets represents a major limitation for its structural optimization. This work describes the use of a molecular modeling approach to rationalize the in vitro antiviral activity of plitidepsin and to identify potent

SUBMITTER: El Hassab MA 

PROVIDER: S-EPMC9011487 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature