Essential oil constituents of regional ethnomedicinal plants as potential inhibitors of SARS-CoV-2 Mpro: an integrated molecular docking, molecular dynamics and QM/MM study.
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引用次数: 0
Abstract
The scientific community has achieved a remarkable milestone by creating efficacious vaccines against the SARS-CoV-2 virus. The treatment alternatives are still restricted, though. The bioactive ingredients present in natural plants are known to exhibit diverse pharmacological effects against many diseases. Using computational techniques such as molecular docking, drug-likeness, ADMET study, MD simulation, and our own N-layered Integrated molecular Orbital and Molecular mechanics (ONIOM) calculations, this study aimed to investigate essential oil constituents of Lindera neesiana, Litsea cubeba and Zanthoxylum armatum DC plants as a potential natural inhibitor of SARS-CoV-2 main protease (Mpro). To determine their binding affinity, 107 phytochemical substances in total were docked inside the binding pocket of Mpro. Copaene showed the highest binding affinity among the 107 compounds, with an energy of -7.90 kcal/mol. Furthermore, physiochemical and ADMET properties were evaluated for the top five phytocompounds. The studied phytocompounds showed good physiochemical and pharmacokinetic behaviour with no associated toxicity. MD simulation further provided evidence for stable interaction of phytocompounds within the binding pocket of Mpro. Subsequently, ONIOM calculation was done on the best-hit complex, wherein the hydrogen bonding interactions were retained with appreciable negative energy. These in silico results indicate that the specific phytocompounds present in essential oils of L. neesiana, L. cubeba, and Z. armatum DC have significant inhibitor ability against SARS-CoV-2 main protease and could be explored for future therapeutic investigations.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.