MolTech Ltd, 119992, Moscow, Leninskie gory, 1/75A, Russia.
J Mol Model. 2010 Jul;16(7):1223-30. doi: 10.1007/s00894-009-0633-8. Epub 2009 Dec 30.
In the current study an innovative method of structural filtration of docked ligand poses is introduced and applied to improve the virtual screening results. The structural filter is defined by a protein-specific set of interactions that are a) structurally conserved in available structures of a particular protein with its bound ligands, and b) that can be viewed as playing the crucial role in protein-ligand binding. The concept was evaluated on a set of 10 diverse proteins, for which the corresponding structural filters were developed and applied to the results of virtual screening obtained with the Lead Finder software. The application of structural filtration resulted in a considerable improvement of the enrichment factor ranging from several folds to hundreds folds depending on the protein target. It appeared that the structural filtration had effectively repaired the deficiencies of the scoring functions that used to overestimate decoy binding, resulting into a considerably lower false positive rate. In addition, the structural filters were also effective in dealing with some deficiencies of the protein structure models that would lead to false negative predictions otherwise. The ability of structural filtration to recover relatively small but specifically bound molecules creates promises for the application of this technology in the fragment-based drug discovery.
在当前的研究中，引入了一种创新的对接配体构象结构过滤方法，并将其应用于改进虚拟筛选结果。结构过滤器由一组特定于蛋白质的相互作用定义，这些相互作用 a）在具有结合配体的特定蛋白质的可用结构中结构上保守，并且 b）可以被视为在蛋白质-配体结合中发挥关键作用。该概念在一组 10 种不同的蛋白质上进行了评估，为这些蛋白质开发了相应的结构过滤器，并将其应用于使用 Lead Finder 软件获得的虚拟筛选结果。结构过滤的应用导致富集因子得到了相当大的提高，根据蛋白质靶标，提高幅度从几倍到几百倍不等。结果表明，结构过滤有效地修复了评分函数的缺陷，这些缺陷过去常常高估诱饵结合，从而导致假阳性率显著降低。此外，结构过滤器在处理一些可能导致假阴性预测的蛋白质结构模型的缺陷方面也非常有效。结构过滤能够恢复相对较小但特异性结合的分子的能力，为该技术在基于片段的药物发现中的应用带来了希望。
