Identification of SARS-CoV-2 main protease inhibitors from FDA-approved drugs by artificial intelligence-supported activity prediction system.

作者信息

Komatsu Hirotsugu, Tanaka Takeshi, Ye Zhengmao, Ikeda Ken, Matsuzaki Takao, Yasugi Mayo, Hosoda Masato

机构信息

Interprotein Corporation, Osaka, Japan.

Graduate School of Life and Environmental Sciences, Osaka Prefecture University, Izumisano, Osaka, Japan.

出版信息

J Biomol Struct Dyn. 2023 Mar;41(5):1767-1775. doi: 10.1080/07391102.2021.2024260. Epub 2022 Jan 5.

Abstract

Although a certain level of efficacy and safety of several vaccine products against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have been established, unmet medical needs for orally active small molecule therapeutic drugs are still very high. As a key drug target molecule, SARS-CoV-2 main protease (M) is focused and large number of screenings, a part of which were supported by artificial intelligence (AI), have been conducted to identify M inhibitors both through drug repurposing and drug discovery approaches. In the many drug-repurposing studies, docking simulation-based technologies have been mainly employed and contributed to the identification of several M binders. On the other hand, because AI-guided INTerprotein's Engine for New Drug Design (AI-guided INTENDD), an AI-supported activity prediction system for small molecules, enables to propose the potential binders by proprietary AI scores but not docking scores, it was expected to identify novel potential M binders from FDA-approved drugs. As a result, we selected 20 potential M binders using AI-guided INTENDD, of which 13 drugs showed M-binding signal by surface plasmon resonance (SPR) method. Six (6) compounds among the 13 positive drugs were identified for the first time by the present study. Furthermore, it was verified that vorapaxar bound to M with a K value of 27 µM by SPR method and inhibited virus replication in SARS-CoV-2 infected cells with an EC value of 11 µM. Communicated by Ramaswamy H. Sarma.

摘要

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