Paul D Sam, Gautham N
Centre of Advanced Study in Crystallography and Biophysics, University of Madras, Chennai 600025, India.
Centre of Advanced Study in Crystallography and Biophysics, University of Madras, Chennai 600025, India.
J Mol Graph Model. 2017 Jun;74:89-99. doi: 10.1016/j.jmgm.2017.03.008. Epub 2017 Mar 18.
We have earlier reported the MOLSDOCK technique to perform rigid receptor/flexible ligand docking. The method uses the MOLS method, developed in our laboratory. In this paper we report iMOLSDOCK, the 'flexible receptor' extension we have carried out to the algorithm MOLSDOCK. iMOLSDOCK uses mutually orthogonal Latin squares (MOLS) to sample the conformation and the docking pose of the ligand and also the flexible residues of the receptor protein. The method then uses a variant of the mean field technique to analyze the sample to arrive at the optimum. We have benchmarked and validated iMOLSDOCK with a dataset of 44 peptide-protein complexes with peptides. We have also compared iMOLSDOCK with other flexible receptor docking tools GOLD v5.2.1 and AutoDock Vina. The results obtained show that the method works better than these two algorithms, though it consumes more computer time.
我们之前报道过用于进行刚性受体/柔性配体对接的MOLSDOCK技术。该方法采用了我们实验室开发的MOLS方法。在本文中，我们报告了iMOLSDOCK，即我们对MOLSDOCK算法进行的“柔性受体”扩展。iMOLSDOCK使用相互正交拉丁方（MOLS）对配体的构象和对接姿势以及受体蛋白的柔性残基进行采样。然后该方法使用平均场技术的一个变体来分析样本以得出最优解。我们用一个包含44个肽 - 蛋白质复合物的数据集对iMOLSDOCK进行了基准测试和验证。我们还将iMOLSDOCK与其他柔性受体对接工具GOLD v5.2.1和AutoDock Vina进行了比较。所得结果表明，该方法比这两种算法效果更好，尽管它消耗更多的计算机时间。
