评估终点方法预测蛋白质激酶抑制剂的结合亲和倾向的能力
Martiniano Bello1, Cindy Bandala2
1Laboratorio de Diseño y Desarrollo de Nuevos Fármacos e Innovación Biotecnológica, Escuela Superior de Medicina, Instituto Politécnico Nacional, Plan de San Luis y Diaz Mirón s/n, Col. Casco de Santo Tomas Ciudad de México 11340 Mexico bellomartini@gmail.com mbellor@ipn.mx.
RSC advances
|August 24, 2023
概括
像MMGBSA和MMPBSA这样的计算方法可以预测酶突变对结合亲和力的影响. 使用MMGBSA进行的长分子动力学模拟与EGFR抑制剂复合物的实验数据有很好的相关性.
科学领域:
- 计算化学和结构生物学
- 分子建模和模拟分子模型
背景情况:
- 对酶突变的实验评估是昂贵的.
- 计算方法,包括分子动力学 (MD) 模拟,用于评估酶突变影响.
- 终点方法估计结合的自由能量 (ΔG),并可以区分连接剂的有效性.
研究的目的:
- 评估MMGBSA和MMPBSA方法对酶突变诱导的亲和力变化的预测能力.
- 为了比较理论预测与野生类型和突变EGFR抑制剂复合物的实验性结合亲和力.
主要方法:
- 选择了十种野生类型和突变EGFR抑制剂复合物,具有已知的实验性结合亲缘关系.
- 进行了分子动力学 (MD) 模拟.
- 应用MMGBSA和MMPBSA计算方法来估计具有约束力的自由能量差异 (ΔΔG).
主要成果:
- MMGBSA,使用100 ns的MD模拟的最后50 ns没有热成分,重现了实验性亲和力趋势 (皮尔森r=0.779,R2=0.606).
- 在使用较短的模拟周期时,MMGBSA和MMPBSA方法都与实验 ΔΔG 值有更好的相关性.
- MMGBSA和MMPBSA对于预测酶突变的相对结合亲缘关系非常有价值.
结论:
- MMGBSA和MMPBSA是有效的计算工具,用于预测激酶突变对抑制剂结合亲和力的影响.
- 优化模拟长度对于使用这些方法进行准确预测至关重要.
- 这些计算方法为酶突变研究的实验查提供了具有成本效益的替代方案.
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