C.A.S. in Crystallography and Biophysics, University of Madras, Maraimalai Campus (Guindy), Chennai, 600025, India.
J Mol Model. 2012 Aug;18(8):3705-22. doi: 10.1007/s00894-012-1369-4. Epub 2012 Mar 1.
Understanding the principles of protein receptor recognition, interaction, and association with molecular substrates and inhibitors is of principal importance in the drug discovery process. MOLSDOCK is a molecular docking method that we have recently developed. It uses mutually orthogonal Latin square sampling (together with a variant of the mean field technique) to identify the optimal docking conformation and pose of a small molecule ligand in the appropriate receptor site. Here we report the application of this method to simultaneously identify both the low energy conformation and the one with the best pose in the case of 62 protein-bound nucleotide ligands. The experimental structures of all these complexes are known. We have compared our results with those obtained from two other well-known molecular docking software, viz. AutoDock 4.2.3 and GOLD 5.1. The results show that the MOLSDOCK method was able to sample a wide range of binding modes for these ligands and also scores them well.
理解蛋白质受体识别、相互作用以及与分子底物和抑制剂的关联的原理，是药物发现过程中的主要重点。MOLSDOCK 是我们最近开发的一种分子对接方法。它使用相互正交的拉丁方采样（结合平均场技术的变体）来识别小分子配体在适当受体部位的最佳对接构象和位置。在这里，我们报告了该方法在同时识别 62 种与蛋白结合的核苷酸配体的低能量构象和最佳构象的应用。所有这些复合物的实验结构都是已知的。我们将我们的结果与另外两种著名的分子对接软件，即 AutoDock 4.2.3 和 GOLD 5.1 的结果进行了比较。结果表明，MOLSDOCK 方法能够为这些配体采样广泛的结合模式，并且评分也很好。
