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生物信息学方法用于发现SARS-CoV-2的NSP6的潜在化合物,使用基于结构的虚拟查和分子动力学模拟

Mohammed M Salama¹, Medhat W Shafaa², Mohamed E El-Nagdy²

¹Physics Department, Medical Biophysics Division, Faculty of Science, Helwan University, Cairo, Egypt. mmhslama@gmail.com.

Scientific reports

|October 28, 2025

概括

研究人员确定了8种潜在的SARS-CoV-2抑制剂,其向非结构性蛋白6 (NSP6),这是一个关键的病毒复制蛋白. 这些化合物显示出作为开发新抗病毒疗法对抗SARS-CoV-2的化合物的前景.

科学领域:

病毒学病毒学
计算化学的计算化学
药物发现药物发现药物发现

背景情况:

非结构性蛋白6 (NSP6) 对于SARS-CoV-2的复制和转录至关重要.
NSP6与西格玛受体1 (SR1) 相互作用,影响内 плазма网膜压力.
准NSP6为开发SARS-CoV-2治疗方法提供了一个有前途的战略.

研究的目的:

使用计算方法识别SARS-CoV-2 NSP6的潜在抑制剂.
评估已确定化合物作为主要候选药物的疗效和安全性.

主要方法:

使用AlphaFold预测NSP6的三级结构,使用DeepRefiner进行精炼.
使用Autodock Vina进行分子对接,对ZINC20数据库进行虚拟选.
接后分析包括能量计算,ADMET研究和100 ns分子动态模拟.

主要成果:

确定了8种潜在的化合物,具有显著的对接分数和结合能.
选择的化合物没有表现出细胞细胞毒性和与NSP6.6的良好相互作用.
分子动态模拟验证了顶级候选复合物的稳定性和结合相互作用.

结论:

化合物ZINC-141,457,420,ZINC-075486396和ZINC-018529632显示出作为SARS-CoV-2NSP6.6抑制剂的显著潜力.
这些已识别的配体代表了进一步开发针对SARS-CoV-2的抗病毒药物的有希望的候选人.
这项研究强调了综合计算方法在针对病毒点的药物发现中的有用性.

关键词:

停靠的对接方式这就是MMPBSA.分子动力学模拟模型在 NSP6 中,NSP6 是指NSP6.这就是SARS-CoV-2病毒.在ZINC20C20中使用.

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