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Abstract
Aim: We seek to provide an understanding of the binding mechanism of Remdesivir, as well as structural and conformational implications on SARS-CoV-2 virus RNA-dependent RNA polymerase upon its binding and identify its crucial pharmacophoric moieties.
Background: The coronavirus disease of 2019 (COVID-19) pandemic had infected over a million people, with 65,000 deaths as of the first quarter of 2020. The current limitation of effective treatment options with no approved vaccine or targeted therapeutics for the treatment of COVID-19 has posed serious global health threats. This has necessitated several drug and vaccine development efforts across the globe. To date, the farthest in the drug development pipeline is Remdesivir.
Objectives: We performed the molecular dynamics simulation, quantified the energy contributions of binding site residues using per-residue energy decomposition calculations, and subsequently generated a pharmacophore model for the identification of potential SARS-CoV-2 virus RNA-dependent RNA polymerase inhibitors.
Methods: Integrative molecular dynamics simulations and thermodynamic calculations coupled with advanced post-molecular dynamics analysis techniques were employed.
Results: Our analysis showed that the modulatory activity of Remdesivir is characterized by an extensive array of high-affinity and consistent molecular interactions with specific active site residues that anchor Remdemsivir within the binding pocket for efficient binding. These residues are ASP452, THR456, ARG555, THR556, VAL557, ARG624, THR680, SER681, and SER682. Results also showed that Remdesivir binding induces minimal individual amino acid perturbations, subtly interferes with deviations of C-α atoms, and restricts the systematic transition of SARS-CoV-2 RNA-dependent RNA polymerase from the “buried” hydrophobic region to the “surface-exposed” hydrophilic region. We also mapped a pharmacophore model based on the observed high-affinity interactions with SARSCoV- 2 virus RNA-dependent RNA polymerase, which showcased the crucial functional moieties of Remdesivir and was subsequently employed for virtual screening.
Conclusion: The structural insights and the provided optimized pharmacophoric model would augment the design of improved analogs of Remdesivir that could expand treatment options for COVID-19.
Keywords: COVID-19, SARS-CoV-2 RNA-dependent RNA polymerase, remdesivir, homology modeling, per-residue energy decomposition, pharmacophore, molecular dynamic simulations.