Ranking protein-protein docking results using steered molecular dynamics and potential of mean force calculations
Ranking protein-protein docking results using steered molecular dynamics and potential of mean force calculations
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DOI：
10.1002/jcc.24412
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发表时间：
2016-07-30
影响因子：
3
通讯作者：
Lill, Markus A.
中科院分区：
文献类型：
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作者：
Kingsley, Laura J.;Esquivel-Rodriguez, Juan;Lill, Markus A.
蛋白质-蛋白质复合物的结晶通常会出现问题，因此通常依赖计算结构模型。此类模型通常使用蛋白质-蛋白质对接算法生成，其中主要挑战之一是从数千个潜在预测中选择哪一个代表最接近天然的复合物。我们已经开发了一种新的技术，涉及使用转向分子动力学（sMD）和伞形采样，以确定近天然的蛋白质-蛋白质对接预测之间的复合物。使用这种技术，我们发现我们的预测和接口RMSD（iRMSD）在十个不同的测试系统之间的强相关性。在两个系统上，我们研究了使用平均力计算的潜力是否可以进一步改善预测结果。我们证明了一个近似的本地（
Crystallization of protein-protein complexes can often be problematic and therefore computational structural models are often relied on. Such models are often generated using protein-protein docking algorithms, where one of the main challenges is selecting which of several thousand potential predictions represents the most near-native complex. We have developed a novel technique that involves the use of steered molecular dynamics (sMD) and umbrella sampling to identify near-native complexes among protein-protein docking predictions. Using this technique, we have found a strong correlation between our predictions and the interface RMSD (iRMSD) in ten diverse test systems. On two of the systems, we investigated if the prediction results could be further improved using potential of mean force calculations. We demonstrated that a near-native (