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Knowledge‐based structural models of SARS‐CoV‐2 proteins and their complexes with potential drugs
Author(s) -
Hijikata Atsushi,
ShionyuMitsuyama Clara,
Nakae Setsu,
Shionyu Masafumi,
Ota Motonori,
Kanaya Shigehiko,
Shirai Tsuyoshi
Publication year - 2020
Publication title -
febs letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.593
H-Index - 257
eISSN - 1873-3468
pISSN - 0014-5793
DOI - 10.1002/1873-3468.13806
Subject(s) - covid-19 , drug repositioning , repurposing , coronavirus , computational biology , pandemic , drug discovery , disease , chemistry , pharmacology , drug , medicine , virology , biology , bioinformatics , infectious disease (medical specialty) , ecology , pathology , outbreak
The World Health Organization (WHO) has declared the coronavirus disease 2019 (COVID‐19) caused by the novel coronavirus SARS‐CoV‐2 a pandemic. There is, however, no confirmed anti‐COVID‐19 therapeutic currently. In order to assist structure‐based discovery efforts for repurposing drugs against this disease, we constructed knowledge‐based models of SARS‐CoV‐2 proteins and compared the ligand molecules in the template structures with approved/experimental drugs and components of natural medicines. Our theoretical models suggest several drugs, such as carfilzomib, sinefungin, tecadenoson, and trabodenoson, that could be further investigated for their potential for treating COVID‐19.