一个热力学循环来预测一个进化的酶的竞争性抑制结果
bioRxiv : the preprint server for biology
|February 20, 2025
概括
了解酶抑制剂相互作用是预测耐药性的关键. 这项研究将竞争性抑制与大肠杆菌DHFR和trimethoprim的自由能量扰动计算联系起来,揭示了对抗性突变的分子洞察力.
科学领域:
- 生物化学 生物化学
- 计算生物学 计算生物学
- 分子进化分子进化
背景情况:
- 竞争性抑制对于理解酶药物相互作用和药物耐药性的演变至关重要.
- 化学自由能量扰动 (FEP) 计算提供了一种强大的计算方法,以在分子水平上研究这些相互作用.
研究的目的:
- 制定一个框架,将竞争抑制与FEP计算联系起来.
- 调查大肠杆菌二水酸还原酶 (DHFR) 中的三甲 (TMP) 耐药性的分子机制.
- 预测抗性突变对酶抑制剂结合和进化适应性的影响.
主要方法:
- 使用的化学自由能量扰动 (FEP) 计算.
- 使用热力学循环将实验约束常数与自由能量差异联系起来.
- 模拟的野生型和突变形式的大肠杆菌DHFR与TMP相互作用.
主要成果:
- 在将约束常数与自由能量差异相关时,达到0.9kcal/mol的平均误差.
- 证明耐药性突变通过结构和动态效应稳定了抑制剂或基质结合状态.
- 在某些突变组合中观察到显著的表皮病.
结论:
- 局部结构动力学在竞争性抑制中发挥着关键作用.
- FEP模拟为突变效应和表观相互作用提供了宝贵的见解.
- 这种集成的计算和实验方法有助于预测耐药性突变的影响和设计治疗方法.
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