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Effect of nelfinavir stereoisomers on coronavirus main protease: Molecular docking, molecular dynamics simulation and MM/GBSA study.
Sargolzaei, Mohsen.
  • Sargolzaei M; Faculty of Chemistry, Shahrood University of Technology, Shahrood, Iran. Electronic address: mohsen.sargolzaei@gmail.com.
J Mol Graph Model ; 103: 107803, 2021 03.
Article in English | MEDLINE | ID: covidwho-957225
ABSTRACT
In this study, the binding strength of 32 diastereomers of nelfinavir, a proposed drug for the treatment of COVID-19, was considered against main protease. Molecular docking was used to determine the most potent diastereomers. The top three diastereomers along with apo form of protein were then considered via molecular dynamics simulation and MM-GBSA method. During the simulation, the structural consideration of four proteins considered was carried out using RMSD, RMSF, Rg and hydrogen bond analysis tools. Our data demonstrated that the effect of nelfinavir RSRSR stereoisomer on protein stability and compactness is higher than the other. We also found from the hydrogen bond analysis that this important diastereomer form three hydrogen bonds with the residues of Glu166, Gly143 and Hie41. MM/GBSA analysis showed that the binding strength of RSRSR is more than other stereoisomers and that the main contributions to binding energy are vdW and electronic terms. The nelfinavir RSRSR stereoisomer introduced in this study may be effective in the treatment of COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Apoproteins / Protease Inhibitors / Nelfinavir / Coronavirus 3C Proteases / SARS-CoV-2 Type of study: Experimental Studies Language: English Journal: J Mol Graph Model Journal subject: Molecular Biology Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Apoproteins / Protease Inhibitors / Nelfinavir / Coronavirus 3C Proteases / SARS-CoV-2 Type of study: Experimental Studies Language: English Journal: J Mol Graph Model Journal subject: Molecular Biology Year: 2021 Document Type: Article