Modeling Protein-Ligand Binding by Mining Minima
Modeling Protein-Ligand Binding by Mining Minima
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DOI：
10.1021/ct100245n
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发表时间：
2010-11-01
影响因子：
5.5
通讯作者：
Potter, Michael J.
中科院分区：
文献类型：
--
作者：
Chen, Wei;Gilson, Michael K.;Potter, Michael J.
本文首次将最小挖掘算法应用于蛋白质小分子结合。这种端点方法使用经验力场和隐式溶剂模型，将蛋白质结合位置视为完全灵活的，并将自由能估计为局部能量势垒的总和。对于三组HIV-1蛋白酶抑制剂和一组磷酸二酯酶10a抑制剂，计算结果与实验结果令人振奋地一致。考察了模型的各个方面对其精度的贡献，发现泊松-玻尔兹曼修正是最关键的。有趣的是，计算出的结合时构型熵的变化大致符合先前观察到的较小主-客体系统的相同的熵-能量相关性。讨论了该方法的优点和缺点，以及提高精度和速度的前景。
We present the first application of the mining minima algorithm to protein small molecule binding. This end-point approach uses an empirical force field and implicit solvent models, treats the protein binding site as fully flexible, and estimates free energies as sums over local energy wells. The calculations are found to yield encouraging agreement with experimental results for three sets of HIV-1 protease inhibitors and a set of phosphodiesterase 10a inhibitors. The contributions of various aspects of the model to its accuracy are examined, and the Poisson-Boltzmann correction is found to be the most critical. Interestingly, the computed changes in configurational entropy upon binding fall roughly along the same entropy-energy correlation previously observed for smaller host-guest systems. Strengths and weaknesses of the method are discussed, as are the prospects for enhancing accuracy and speed.