Screening and Molecular Modeling Evaluation of Food Peptides to Inhibit Key Targets of COVID-19 Virus

文献类型： 外文期刊

第一作者： Shi, Ai-Min

作者： Shi, Ai-Min;Guo, Rui;Wang, Qiang;Zhou, Jin-Rong

作者机构：

关键词： food peptides; COVID-19 virus; molecular docking; molecular dynamic simulation

期刊名称：BIOMOLECULES （ 影响因子：4.879； 五年影响因子：5.362 ）

ISSN：

年卷期： 2021 年 11 卷 2 期

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收录情况： SCI

摘要： Peptide drugs, especially food-derived peptides, have a variety of functional activities including antiviral and may also have a therapeutic effect on COVID-19. In this study, comparing with the reported drugs, 79 peptides were found to bind to the key targets of COVID-19 virus with higher non-covalent interaction, while among them, six peptides showed high non-covalent interactions with the three targets, which may inhibit the COVID-19 virus. In the simulation, peptides of nine to 10 amino acids with a hydrophilic amino acid and acidic amino acid in the middle and aromatic amino acids on the side showed higher binding to angiotensin-converting enzyme 2 (ACE2). Peptides of five to six amino acids with a basic amnio acid in the head, acidic amnio acid in the neck, hydrophobicity group in the middle, and basic amino acids in the tail showed higher binding to COVID-19 virus main protease (M-pro), while those with basic amino acids and acidic amino acids in the two sides and aromatic amino acids in the middle might have stronger interaction with COVID-19 virus RNA-dependent RNA polymerase (RdRp).

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