Mutational Locally Enhanced Sampling (MULES) for quantitative prediction of the effects of mutations at protein-protein interfaces
Mutational Locally Enhanced Sampling (MULES) for quantitative prediction of the effects of mutations at protein-protein interfaces
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DOI：
10.1039/c2sc00895e
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发表时间：
2012-01-01
期刊：
影响因子：
8.4
通讯作者：
Gould, Ian R.
中科院分区：
文献类型：
--
作者：
Bradshaw, Richard T.;Aronica, Pietro G. A.;Gould, Ian R.
我们已经成功地开发和实验验证了一种新的计算方法，用于定量预测突变在蛋白质-蛋白质界面的影响。从超过500 ns的明确溶剂化的分子动力学，突变局部增强采样（MULES）显示出显着提高的准确性比后处理方法的原型突变集，与实验的最大平均无符号误差为0.5 kcal mol（-1）和可比或更好的精度。该技术原则上允许计算任何突变的影响，无论是自然的还是非自然的。与现有的计算预测技术相比，MULES的多功能性、定量准确性、高精度和速度增强了其以系统的方式模拟界面变化的潜力，从而有助于肽和蛋白质相互作用设计。
We have successfully developed and validated with experiment a new computational method for quantitatively predicting the effects of mutations at a protein-protein interface. From over 500 ns of explicitly solvated molecular dynamics, Mutational Locally Enhanced Sampling (MULES) shows significantly improved accuracy over post-processing methods for a prototypical set of mutations, with a maximum mean unsigned error to experiment of 0.5 kcal mol(-1) and comparable or better precision. The technique in principle allows the effect of any mutation to be calculated, whether natural or non-natural. The versatility, quantitative accuracy, high precision and speed of MULES compared to existing computational prediction techniques enhance its potential for modelling changes to the interface in a systematic way, thereby aiding peptide and protein interaction design.