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通过虚拟查和分子动力学模拟,发现潜在的GPRC5D抑制剂

Xi Chen^1,2, Xinle Yang³, Roufen Chen⁴

¹Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310003, China.

|September 7, 2025

概括

研究人员确定了G蛋白结合受体家族C,组5,成员D (GPRC5D) 的潜在小分子抑制剂,GPRC5D是多发性髓瘤的关键标. 这项计算研究为发现针对GPRC5D的治疗方法提供了一种新方法.

科学领域:

计算化学是一种计算化学.
药理学药理学是指药理学的学科.
在瘤学瘤学.

背景情况:

G蛋白结合受体家族C,第5组,成员D (GPRC5D) 是血液恶性瘤,特别是多发性骨髓瘤的有前途的免疫治疗点.
之前没有系统的虚拟查研究确定了GPRC5D的小分子抑制剂.

研究的目的:

开发和应用一种计算策略,用于识别针对GPRC5D的小分子抑制剂.
发现新型GPRC5D向治疗血液恶性瘤的新疗法.

主要方法:

一个多步骤的虚拟选工作流程,集成了PLANET,Vina-GPU,MM/GBSA和admetSAR 3.0.0.
用于验证的分子动力学 (MD) 模拟和绝对结合自由能量 (ABFE) 计算.
一个8617个组合图书馆的选.

主要成果:

从最初的库中优先考虑了四个候选化合物 (1,2,7和8).
化合物2表现出强大的结合亲和力 (MM/GBSA ΔG = -79.8 kcal/mol,ABFE = -9.0 kcal/mol) 和高度的药物相似性 (QED = 0.670).
MD模拟证实了化合物2与关键残留物ASP238和ASP239.9的稳定相互作用.

结论:

该研究成功建立了一个系统的虚拟查工作流程,用于发现GPRC5D抑制剂.
这种方法有助于识别多发性骨髓瘤和其他血液恶性瘤的潜在GPRC5D向治疗方法.

关键词:

在GPRC5D中使用.深度学习是一种深度学习.分子动力学分子动力学虚拟选虚拟选虚拟选

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