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通过机器学习和实验验证,发现具有抗流感作用的TRPV4向小分子

Yan Sun^1,2, Jiajing Wu², Beilei Shen²

¹College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030801, China.

International journal of molecular sciences

|February 13, 2025

概括

我们开发了一个机器学习模型来识别抑制TRPV4通道的药物,TRPV4通道是流感病毒感染的关键因素. 这种方法确定了glecaprevir和everolimus作为抗流感有前途的抗病毒药物.

科学领域:

* 分子生物学 * 分子生物学
* 病毒学病毒学
* 计算化学计算化学

背景情况:

* 暂时受体潜在化物4 (TRPV4) 通道对于细胞平衡和免疫调节至关重要.
*已知TRPV4激活可增强流感A病毒的复制和传播.
*需要针对TRPV4通道的新型抗病毒策略.

研究的目的:

* 开发第一个用于预测TRPV4抑制小分子的机器学习模型.
* 识别潜在的针对流感的抗病毒效果的重用药物.
* 在体外和体内验证已识别的抑制剂的疗效.

主要方法:

* 开发用于TRPV4抑制剂预测的机器学习模型.
* 开源分子数据库的高通量虚拟选.
* 选择的小分子抗流感药物的体外和体内抗病毒测试.
* 药物标相互作用的机制验证.

主要成果:

* 一个新的机器学习模型成功预测了TRPV4抑制剂.
*虚拟选发现了有前途的候选分子.
* 格莱卡普雷维尔和埃弗罗利斯在体外和体内显著抑制了流感病毒.
*这些药物显著提高了流感感染小鼠的生存率,其保护率分别为80%和100%.

结论:

*TRPV4抑制是开发新型流感抗病毒疗法的可行策略.
*开发的机器学习模型提供了一种快速方法来识别潜在的候选药物.
* 这项研究为未来对TRPV4向抗病毒治疗的临床研究奠定了基础.

关键词:

这是H1N1流感.在 TRPV4 中.抗流感药是一种抗流感药.机器学习是机器学习.分子对接的分子对接.改变药物的用途.

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