谷歌浏览器插件
订阅小程序
在清言上使用

Main Protease Inhibitors and Drug Surface Hotspots for the Treatment of COVID-19: A Drug Repurposing and Molecular Docking Approach

Biomedicine & pharmacotherapy(2021)

引用 20|浏览9
暂无评分
摘要
The world is facing an unprecedented global pandemic caused by the novel SARS-CoV-2. In the absenceof a specific therapeutic agent to treat COVID-19 patients, the present study aimed to virtually screen outthe effective drug candidates from the approved main protease protein (MPP) inhibitors and theirderivatives for the treatment of SARS-CoV-2. Here, drug repurposing and molecular docking wereemployed to screen approved MPP inhibitors and their derivatives. The approved MPP inhibitors againstHIV and HCV were prioritized, whilst hydroxychloroquine, favipiravir, remdesivir, and alpha-ketoamidewere studied as control. The target drug surface hotspot was also investigated through the moleculardocking technique. ADME analysis was conducted to understand the pharmacokinetics and drug-likenessof the screened MPP inhibitors. The result of this study revealed that Paritaprevir (-10.9 kcal/mol), and itsanalog (CID 131982844)(-16.3 kcal/mol) showed better binding affinity than the approved MPP inhibitorcompared in this study including favipiravir, remdesivir, and alpha-ketoamide. A comparative study amongthe screened putative MPP inhibitors revealed that amino acids T25, T26, H41, M49, L141, N142, G143,C145, H164, M165, E166, D187, R188, and Q189 are at critical positions for becoming the surface hotspotin the MPP of SARS-CoV-2. The study also suggested that paritaprevir and its' analog (CID 131982844),may be effective against SARS-CoV-2 as these molecules had the common drug-surface hotspots on themain protease protein of SARS-CoV-2. Other pharmacokinetic parameters also indicate that paritaprevirand its top analog (CID 131982844) will be either similar or better-repurposed drugs than already approvedMPP inhibitors.
更多
查看译文
关键词
Main protease protein (MPP) inhibitors,SARS-CoV-2,COVID-19,Drug repurposing,Molecular docking
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