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Computational assessment of herbal medicine-derived compounds as potential inhibitors of SARS-CoV-2 main protease.
Tao, Yulian; Qu, Hanyang; Wang, Shengpeng; Yan, Fei; Wang, Cuihong; Zhang, Meiling.
  • Tao Y; School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
  • Qu H; School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
  • Wang S; School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
  • Yan F; School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
  • Wang C; School of Science, Tianjin Chengjian University, Tianjin, China.
  • Zhang M; School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
J Biomol Struct Dyn ; : 1-12, 2022 Nov 14.
Article in English | MEDLINE | ID: covidwho-2106894
ABSTRACT
Since the main protease (Mpro) is crucial for the COVID-19 virus replication and transcription, searching for Mpro inhibitors is one possible treatment option. In our study, 258 small molecules were collected from lung-related herbal medicines, and their structures were optimized with the B3LYP-D3/6-31G* method. After the molecular docking with Mpro, we selected the top 20 compounds for the further geometry optimization with the larger basis sets. After the further molecular docking, the top eight compounds were screened out. Then we performed molecular dynamics simulations and binding free energy calculations to determine stability of the complexes. Our results show that mulberrofuran G, Xambioona, and kuwanon D can bind Mpro well. In quantum chemistry studies, such as ESP and CDFT analyses, the compounds properties are predicted. Additionally, the drug-likeness analyses and ADME studies on these three candidate compounds verified that all of them conform to Libinski's rule and may be drug-like compounds.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Traditional medicine Language: English Journal: J Biomol Struct Dyn Year: 2022 Document Type: Article Affiliation country: 07391102.2022.2144949

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Traditional medicine Language: English Journal: J Biomol Struct Dyn Year: 2022 Document Type: Article Affiliation country: 07391102.2022.2144949