In silico identification of potential inhibitors against main protease of SARS-CoV-2 6LU7 from Andrographis panniculata via molecular docking, binding energy calculations and molecular dynamics simulation studies

Saudi Journal of Biological Sciences(2022)

引用 14|浏览8
暂无评分
摘要
Background: The ongoing global outbreak of new corona virus (SARS-CoV-2) has been recognized as global public health concern since it causes high morbidity and mortality every day. Due to the rapid spreading and re-emerging, we need to find a potent drug against SARS-CoV-2. Synthetic drugs, such as hydroxychloroquine, remdisivir have paid more attention and the effects of these drugs are still under investigation, due to their severe side effects. Therefore, the aim of the present study was performed to identify the potential inhibitor against main protease SARS-CoV-2 6LU7. Objective: In this study, RO5, ADME properties, molecular dynamic simulations and free binding energy prediction were mainly investigated. Results: The molecular docking study findings revealed that andrographolide had higher binding affinity among the selected natural diterpenoids compared to co-crystal native ligand inhibitor N3. The persistent inhibition of Ki for diterpenoids was analogous. Furthermore, the simulations of molecular dynamics and free binding energy findings have shown that andrographolide possesses a large amount of dynamic properties such as stability, flexibility and binding energy. Conclusion: In conclusion, findings of the current study suggest that selected diterpenoids were predicted to be the significant phytonutrient-based inhibitor against SARS-CoV-2 6LU7 (Mpro). However, preclinical and clinical trials are needed for the further scientific validation before use. (c) 2021 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
更多
查看译文
关键词
Corona,SARS-CoV-2,COVID-19 (6LU7),Natural compounds,Diterpenoids,Andrographolide,Molecular dynamic simulations
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要