The RNA-dependent RNA polymerase (RdRp) of the SARS-CoV-2 is currently an important target in drug discovery for the treatment of COVID-19. Molnupiravir, a broad-spectrum antiviral originally produced by Merck to treat influenza, was found to reduce hospitalizations by 50%, according to phase three clinical trials. Also, no deaths were reported in patients who received the “COVID-19 pill”. It is an orally bioavailable prodrug of the nucleoside analog β-D-N4-hydroxycytidine (NHC), which increases G to A and C to U transition mutations in replicating coronaviruses. Herein, we used molecular docking (PDB: 7BV2) to predict its binding modes at the active site of RdRp. Then, temperature-dependent dynamics simulations were performed in 300, 310, and 313K to understand the inhibition of NHC with increasing temperature. Finally, DFT/B3LYP calculations were used to obtain binding energy values for each complex. Initially, NHC binds at the catalytic site with a similar binding mode to remdesivir (RMSD: 0.51Å). Then, dynamics simulations in different temperatures demonstrated that RdRp at 300 and 310K exhibits similar behaviors (RMSD between 0.2-0.25Å, within 20000 ps). In contrast, RdRp at 313K presents RMSD values varying from 0.18 to 0.35Å up to 5500 ps and, then it stabilizes similarly to the other two temperatures. It could be associated with NHC fluctuations at the same simulation time since it presents a higher freedom degree at 313K. Finally, DFT calculations revealed that NHC presents the most stable conformation at 313K, suggesting which it is truly effective in febrile patients, as observed in phase III studies.
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Exploring molnupiravir (EIDD-2801) by molecular docking, temperature-dependent dynamics simulations, and DFT calculations on the RNA-dependent RNA polymerase (RdRp) from SARS-CoV-2
Published:
02 November 2021
by MDPI
in 7th International Electronic Conference on Medicinal Chemistry
session Round table on predictive tools
Abstract:
Keywords: Antiviral; binding mode; conformations; drug metabolism; EIDD-2801; in silico; NHC