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Investigation of Bucillamine as anti-COVID-19 drug: DFT study, molecular docking, molecular dynamic simulation and ADMET analysis.
Huang, Fengwen; Chen, Chen.
  • Huang F; Key Laboratory of Neuroscience, Department of Biomedical Science, City University of HongKong, Hong Kong, China.
  • Chen C; Shenzhen Key Laboratory of Marine Bioresources and Ecology, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China.
J Biomol Struct Dyn ; : 1-9, 2023 Mar 30.
Article in English | MEDLINE | ID: covidwho-2263426
ABSTRACT
The novel coronavirus disease-2019 (COVID-19), caused by SARS-CoV-2, is a global health pandemic beginning in early December 2019 in Wuhan, Hubei province, China. The effective drug target among coronaviruses is the SARS-CoV-2 main protease (Mpro), because of its crucial role in processing viral polyproteins translated from the viral RNA. In this study, the bioactivity of the selected thiol drug named Bucillamine (BUC) was evaluated as a potential drug for COVID-19 treatment by using computational modeling strategies. First, the molecular electrostatic potential density (ESP) calculation was performed to estimate the chemically active atoms of BUC. Additionally, BUC was docked to the Mpro (PDB 6LU7) to evaluate the protein-ligand binding affinities. Besides, the estimated ESP results by density functional theory (DFT) were used to illustrate the molecular docking findings. Moreover, the frontier orbitals analysis was calculated to determine the charge transfer between the Mpro and BUC. Then, the stability of protein-ligand complex was subjected to the molecular dynamic simulations. Finally, an in silico study was performed to predict drug-likeness and absorption, distribution, metabolism, excretion and toxicity profiles (ADMET) of BUC. These results propose that BUC can be a potential drug candidate against the COVID-19 disease progression.Communicated by Ramaswamy H. Sarma.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: J Biomol Struct Dyn Year: 2023 Document Type: Article Affiliation country: 07391102.2023.2192791

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: J Biomol Struct Dyn Year: 2023 Document Type: Article Affiliation country: 07391102.2023.2192791