Identification of bioactive molecules from Triphala (Ayurvedic herbal formulation) as potential inhibitors of SARS-CoV-2 main protease (Mpro) through computational investigations.

通过计算研究鉴定三果宝(阿育吠陀草药配方)中的生物活性分子作为 SARS-CoV-2 主蛋白酶 (Mpro) 的潜在抑制剂

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作者:Rudrapal Mithun, Celik Ismail, Khan Johra, Ansari Mohammad Azam, Alomary Mohammad N, Yadav Rohitash, Sharma Tripti, Tallei Trina Ekawati, Pasala Praveen Kumar, Sahoo Ranjan Kumar, Khairnar Shubham J, Bendale Atul R, Zothantluanga James H, Chetia Dipak, Walode Sanjay G
Severe acute respiratory syndrome coronavirus disease (SARS-CoV-2) induced coronavirus disease 2019 (COVID-19) pandemic is the present worldwide health emergency. The global scientific community faces a significant challenge in developing targeted therapies to combat the SARS-CoV-2 infection. Computational approaches have been critical for identifying potential SARS-CoV-2 inhibitors in the face of limited resources and in this time of crisis. Main protease (M(pro)) is an intriguing drug target because it processes the polyproteins required for SARS-CoV-2 replication. The application of Ayurvedic knowledge from traditional Indian systems of medicine may be a promising strategy to develop potential inhibitor for different target proteins of SARS-CoV-2. With this endeavor, we docked bioactive molecules from Triphala, an Ayurvedic formulation, against M(pro) followed by molecular dynamics (MD) simulation (100 ns) to investigate their inhibitory potential against SARS-CoV-2. The top four best docked molecules (terflavin A, chebulagic acid, chebulinic acid, and corilagin) were selected for MD simulation study and the results obtained were compared to native ligand X77. From docking and MD simulation studies, the selected molecules showed promising binding affinity with the formation of stable complexes at the active binding pocket of M(pro) and exhibited negative binding energy during MM-PBSA calculations, indication their strong binding affinity with the target protein. The identified bioactive molecules were further analyzed for drug-likeness by Lipinski's filter, ADMET and toxicity studies. Computational (in silico) investigations identified terflavin A, chebulagic acid, chebulinic acid, and corilagin from Triphala formulation as promising inhibitors of SARS-CoV-2 M(pro), suggesting experimental (in vitro/in vivo) studies to further explore their inhibitory mechanisms.

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