一个热力学循环来预测一个进化的酶的竞争性抑制结果
Ebru Cetin1, Haleh Abdizadeh1, Ali Rana Atilgan1
1Faculty of Engineering and Natural Sciences, Sabanci University, 34956 Istanbul, Türkiye.
Journal of chemical theory and computation
|April 23, 2025
概括
我们开发了一种计算方法来预测酶突变如何导致药物耐药性. 这种方法准确地模拟了竞争性抑制,这对于理解酶抑制剂动态和演变至关重要.
科学领域:
- 生物化学 生物化学
- 计算生物学 计算生物学
- 酶动力学 酶动力学
背景情况:
- 竞争性抑制是酶抑制剂动态和耐药性的关键.
- 了解分子相互作用有助于预测抗性突变的进化结果.
研究的目的:
- 建立一个计算框架,将竞争性抑制与化学自由能量扰动 (FEP) 计算联系起来.
- 调查大肠杆菌二叶酸减少酶 (DHFR) 中的三甲 (TMP) 耐药性的分子基础.
主要方法:
- 利用热力学循环将实验结合常量 (Ki和Km) 与自由能量差异连接起来.
- 用于野生类型和突变DHFR的化学自由能量扰动 (FEP) 模拟.
- 综合计算和实验数据,进行可靠的分析.
主要成果:
- 在将绑定常数与自由能量差异相关时,达到0.9kcal/mol的平均误差.
- 证明耐药性突变会对基质和抑制剂的结合 afinities 有不同的影响.
- 发现突变通过结构/动态效应稳定了抑制剂或基质结合状态,突出了分子表观症.
结论:
- FEP框架提供了对抗性突变对酶功能和健康的影响的准确预测.
- 这种方法提供了对突变效应和表观相互作用的精确解释.
- 洞察力促进了针对耐药细菌菌株的改进治疗策略的设计.
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