Knowledge‐based structural models of SARS‐CoV‐2 proteins and their complexes with potential drugs,FEBS Letters

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Knowledge‐based structural models of SARS‐CoV‐2 proteins and their complexes with potential drugs
FEBS Letters ( IF 3.0 ) Pub Date : 2020-05-25 , DOI: 10.1002/1873-3468.13806
Atsushi Hijikata ₁ , Clara Shionyu-Mitsuyama ₁ , Setsu Nakae ₁ , Masafumi Shionyu ₁ , Motonori Ota ₂ , Shigehiko Kanaya ₃ , Tsuyoshi Shirai ₁

Affiliation

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.

中文翻译：

基于知识的 SARS-CoV-2 蛋白结构模型及其与潜在药物的复合物

世界卫生组织 (WHO) 已宣布由新型冠状病毒 SARS-CoV-2 引起的 2019 年冠状病毒病 (COVID-19) 为大流行病。然而，目前还没有确认的抗 COVID-19 治疗药物。为了帮助基于结构的发现努力重新利用针对这种疾病的药物，我们构建了基于知识的 SARS-CoV-2 蛋白模型，并将模板结构中的配体分子与已批准/实验药物和天然药物成分进行了比较。我们的理论模型表明，卡非佐米、sinefungin、tecadenoson 和 trabodenoson 等几种药物可以进一步研究其治疗 COVID-19 的潜力。

更新日期：2020-05-25

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