人工智能引导的结合机制和MERS-CoV的分子动力学
Pradyumna Kumar1, Lingtao Chen1, Rachel Yuanbao Chen2
1College of Computing and Software Engineering, Kennesaw State University, Marietta, GA 30060, USA.
International journal of molecular sciences
|February 27, 2026
概括
中东呼吸综合征冠状病毒 (MERS-CoV) 进入人体细胞取决于DPP4受体相互作用. 分子动力学模拟确定了MERS-CoV-DPP4结合的关键残留物,有助于抗病毒药物设计.
科学领域:
- 病毒学和计算生物学
- 药物发现和开发 药物发现和开发
背景情况:
- 中东呼吸综合征冠状病毒 (MERS-CoV) 由于其高死亡率和有限的治疗选择,构成了严重的公共卫生威胁.
- 病毒进入机制,特别是MERS-CoV表面蛋白与人类二乙酶-4 (DPP4) 受体之间的相互作用,对于理解和对抗感染至关重要.
研究的目的:
- 使用计算方法识别参与MERS-CoV和DPP4受体相互作用的关键接口残留物.
- 为开发针对MERS-CoV.针对性的抗病毒疗法提供分子基础.
主要方法:
- 在高性能计算 (HPC) 平台上利用分子动力学 (MD) 模拟来分析MERS-CoV-DPP4相互作用.
- 通过分析盐桥和键占用率,确定了关键的残留物对.
- 在人体温度和压力下通过独立的MD模拟验证了残留物稳定性.
- 计算结合亲缘关系以量化相互作用强度.
主要成果:
- 确定了MERS-CoV和DPP4受体之间的七个关键相互作用对.
- 证实了之前报告的两个相互作用对 (Asp510-Arg317和Arg511-Asp393).
- 提出了五种新的相互作用对,用于未来在抗病毒药物发现中的实验验证.
结论:
- 这项研究为MERS-CoV-DPP4结合机制提供了关键的分子洞察力.
- 这些发现支持基于结构的抑制剂的合理设计,以破坏病毒的进入.
- 这项研究有助于将计算发现转化为潜在的MERS-CoV抗病毒疗法.
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