http://scholars.ntou.edu.tw/handle/123456789/19011
標題: | In silico identification of drug candidates against COVID-19 | 作者: | Yifei Wu Kuan Y. Chang Lei Lou Lorette G. Edwards Bly K. Doma Zhong-Ru Xie |
關鍵字: | COVID-19;Ligand-protein docking;Virtual screening;Remdesivir;Drug repurposing;Main protease;RNA-dependent RNA polymerase | 公開日期: | 2020 | 出版社: | ELSEVIER | 卷: | 21 | 來源出版物: | Informatics in Medicine Unlocked | 摘要: | The COVID-19 pandemic has caused unprecedented health and economic crisis throughout the world. However, there is no effective medication or therapeutic strategy for treatment of this disease currently. Here, to elucidate the inhibitory effects, we first tested binding affinities of 11 HIV-1 protease inhibitors or their pharmacoenhancers docked onto SARS-CoV-2 main protease (Mpro), and 12 nucleotide-analog inhibitors docked onto RNA dependent RNA polymerase (RdRp). To further obtain the effective drug candidates, we screened 728 approved drugs via virtual screening on SARS-CoV-2 Mpro. Our results demonstrate that remdesivir shows the best binding energy on RdRp and saquinvir is the best inhibitor of Mpro. Based on the binding energies, we also list 10 top-ranked approved drugs which can be potential inhibitors for Mpro. Overall, our results do not only propose drug candidates for further experiments and clinical trials but also pave the way for future lead optimization and drug design. |
URI: | http://scholars.ntou.edu.tw/handle/123456789/19011 | DOI: | 10.1016/j.imu.2020.100461 |
顯示於: | 資訊工程學系 |
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