Adopting Autodock Koto for Virtual Screening of COVID-19

Zhangfan Yang, Kun Cao, Junkai Ji, Zexuan Zhu, Jianqiang Li

Abstract: COVID-19 is a highly contagious virus that causes respiratory diseases in humans. Responding quickly to such pathogen is crucial to stop the uncontrolled spread of diseases. Through computational approaches, repurposing existing drugs is an efficient and effective way to provide treatments. In this study, a powerful docking program named Autodock Koto, proposed in our previous research, is used to virtually screen antiviral drugs for SARS-CoV-2. It identified new uses of drugs that have safety profiles and well-established pharmacology. Several vital target proteins have been considered in our experiments, such as Spike, 3-chymotrypsin-like protease (3CLpro), and RNA-dependent RNA polymerase (RdRp). Experimental results demonstrate that Nystatin, Amphotericin B, Hypericin, Ergotamine, Natamycin and Teicoplanin have the potential as antiviral drugs for the treatment of SARS-CoV-2, and are worth further in-vitro or clinical trials. In addition, the interactions between the drugs and corresponding target proteins have also been analyzed in this study.