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Knowledge-Based Structural Models of SARS-CoV-2 Proteins and Their Complex with Potential Drugs
preprintsubmitted on 24.03.2020, 03:44 and posted on 24.03.2020, 08:23 by Atsushi Hijikata, Clara Shionyu-Mitsuyama, Setsu Nakae, Masafumi Shionyu, Motonori Ota, Shigehiko Kanaya, Tsuyoshi Shirai
The World Health Organization (WHO) has declared a pandemic of the 2019 novel cornavirus SARS-CoV-2 infection (COVID-19). There is, however, no confirmed anti-COVID-19 therapeutic currently. In order to assist structure-based discovery of repurposing drugs against this disease, knowledge-based models of SARS-CoV-2 proteins were constructed using MODELLER software, and their models were refined by PHENIX and COOT. The model quality was assessed with MolProbity. The ligand molecules in the template structures were compared with approved/experimental drugs and components of natural medicines from the KEGG and KNApSAcK databases. The models suggested several drugs, such as carfilzomib, sinefungin, tecadenoson, and trabodenoson, as potential drugs for COVID-19.