Komatsu Hirotsugu, Tanaka Takeshi, Ye Zhengmao, Ikeda Ken, Matsuzaki Takao, Yasugi Mayo, Hosoda Masato
Interprotein Corporation, Osaka, Japan.
Graduate School of Life and Environmental Sciences, Osaka Prefecture University, Izumisano, Osaka, Japan.
J Biomol Struct Dyn. 2023 Mar;41(5):1767-1775. doi: 10.1080/07391102.2021.2024260. Epub 2022 Jan 5.
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.
尽管几种针对严重急性呼吸综合征冠状病毒2（SARS-CoV-2）的疫苗产品已确立了一定水平的疗效和安全性，但口服活性小分子治疗药物的未满足医疗需求仍然很高。作为关键的药物靶标分子，SARS-CoV-2主要蛋白酶（M）受到关注，并通过药物重新利用和药物发现方法进行了大量筛选，其中一部分得到了人工智能（AI）的支持，以鉴定M抑制剂。在许多药物重新利用研究中，主要采用了基于对接模拟的技术，并有助于鉴定几种M结合剂。另一方面，由于人工智能指导的新型药物设计蛋白质间引擎（AI-guided INTENDD），一种用于小分子的人工智能支持的活性预测系统，能够通过专有的人工智能分数而不是对接分数提出潜在的结合剂，因此有望从美国食品药品监督管理局（FDA）批准的药物中鉴定出新的潜在M结合剂。结果，我们使用AI-guided INTENDD选择了20种潜在的M结合剂，其中13种药物通过表面等离子体共振（SPR）方法显示出M结合信号。本研究首次鉴定出13种阳性药物中的6种化合物。此外，通过SPR方法验证了vorapaxar与M结合的K值为27µM，并在SARS-CoV-2感染的细胞中以11µM的EC值抑制病毒复制。由拉马斯瓦米·H·萨尔马传达。
