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利用人工智能精确探索N蛋白向南丁SARS-CoV-2抑制剂:一种新的方法

Zheng-Rui Xiang¹, Shi-Rui Fan¹, Juan Ren²

¹State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, 650201, China; Research Unit of Chemical Biology of Natural Anti-Virus Products, Chinese Academy of Medical Sciences, Beijing, 100730, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, 650204, China.

European journal of medicinal chemistry

|September 22, 2024

概括

研究人员利用深度学习来设计针对SARS-CoV-2 N蛋白质的新型化合物,这是一个关键的病毒成分. 化合物38对COVID-19表现出显著的结合和抗病毒活性,提供了一个新的治疗策略.

科学领域:

病毒学病毒学
药物发现药物发现药物发现
计算化学计算化学

背景情况:

新型冠状病毒 (SARS-CoV-2) 由于持续的突变,继续构成威胁.
关于SARS-CoV-2治疗方法的研究主要集中在功能性蛋白质上,像N蛋白质这样的结构性蛋白质受到的关注较少.
准N蛋白为新型抗COVID-19药物开发提供了潜在的途径.

研究的目的:

调查针对SARS-CoV-2 N蛋白质进行治疗干预的潜力.
利用深度学习模型优化和设计新型抗病毒化合物.
为了识别和验证N蛋白的功能强大的抑制剂.

主要方法:

利用深度学习模型 (EMPIRE,DeepFrag) 来优化基于氨酸的化合物.
对超过10,000个深度学习衍生小分子进行了高通量虚拟选.
合成了44种化合物,并使用分子对接,表面等离子体共振 (SPR) 和微尺度热泳 (MST) 验证了结合亲和力.

主要成果:

化合物38与N蛋白的结合能量为-8.2 kcal/mol,离合常数为353 nM (SPR) 和726 nM (MST).
化合物38在体外表现出对SARS-CoV-2的抗病毒活性.
该化合物干扰了N蛋白与RNA的结合,抑制了病毒复制.

结论:

SARS-CoV-2 N 蛋白质是抗COVID-19 药物开发的可行的治疗标.
深度学习模型是加速设计和发现主要抗病毒化合物的有效工具.
化合物38是作为抗病毒剂进一步开发的有希望的候选物.

关键词:

深度学习是一种深度学习.核体蛋白质是一种核体蛋白质.南里丁 (Phenanthridine) 是一种类型的药物.这就是SARS-CoV-2病毒.

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