4.4 Article

Virtual screening, ADMET profiling, PASS prediction, and bioactivity studies of potential inhibitory roles of alkaloids, phytosterols, and flavonoids against COVID-19 main protease (Mpro)

期刊

NATURAL PRODUCT RESEARCH
卷 36, 期 12, 页码 3110-3116

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/14786419.2021.1935933

关键词

Virtual screening; SARS-CoV-2; COVID-19; phytochemicals; molecular docking; density functional method

向作者/读者索取更多资源

The current research utilized virtual screening to study 57 isolated phytochemicals against the SARS-CoV-2 main protease, identifying several potential inhibitors with good bioactivity and drug-likeness properties. These compounds could be promising candidates for the development of new therapeutic agents against SARS-CoV-2.
The current research used a virtual screening method to study 57 isolated phytochemicals (alkaloids, phytosterols, and flavonoids) against the SARS-CoV-2 main protease (M-pro). The absorption, distribution, metabolism, excretion, and toxicity (ADMET) of the selected compounds were analysed using admetSAR tool while SwissADME and Molinspiration chemoinformatics tools were used to examine the oral bioavailability and drug-likeness properties. Parameters such as physicochemical properties, activity spectra for substances (PASS) prediction, bioactivity, binding mode, and molecular interactions were also analysed. Our results favoured Lupeol (-8.6 kcal/mol), Lupenone (-7.7 kcal/mol), Hesperetin (-7.4 kcal/mol), Apigenin (-7.3 kcal/mol) and Castasterone (-7.3 kcal/mol) as probable inhibitors of SARS-CoV-2. This is because of their good binding affinities, bioactivities, drug-likeness, ADMET properties, PASS properties, oral bioavailability, binding mode and their interactions with the active site of the target receptor compared to Remdesivir and Azithromycin. Therefore, these compounds could be explored towards the development of new therapeutic agents against SARS-CoV-2.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据