Balius Trent E, Mukherjee Sudipto, Rizzo Robert C
Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794.
J Comput Chem. 2011 Jul 30;32(10):2273-89. doi: 10.1002/jcc.21814. Epub 2011 May 3.
A docking-rescoring method, based on per-residue van der Waals (VDW), electrostatic (ES), or hydrogen bond (HB) energies has been developed to aid discovery of ligands that have interaction signatures with a target (footprints) similar to that of a reference. Biologically useful references could include known drugs, inhibitors, substrates, transition states, or side-chains that mediate protein-protein interactions. Termed footprint similarity (FPS) score, the method, as implemented in the program DOCK, was validated and characterized using: (1) pose identification, (2) crossdocking, (3) enrichment, and (4) virtual screening. Improvements in pose identification (6–12%) were obtained using footprint-based (FPS(VDW+ES)) vs. standard DOCK (DCE(VDW+ES)) scoring as evaluated on three large datasets (680–775 systems) from the SB2010 database. Enhanced pose identification was also observed using FPS (45.4% or 70.9%) compared with DCE (17.8%) methods to rank challenging crossdocking ensembles from carbonic anhydrase. Enrichment tests, for three representative systems, revealed FPSVDW+ES scoring yields significant early fold enrichment in the top 10% of ranked databases. For EGFR, top FPS poses are nicely accommodated in the molecular envelope defined by the reference in comparison with DCE, which yields distinct molecular weight bias toward larger molecules. Results from a representative virtual screen of ca. 1 million compounds additionally illustrate how ligands with footprints similar to a known inhibitor can readily be identified from within large commercially available databases. By providing an alternative way to rank ligand poses in a simple yet directed manner we anticipate that FPS scoring will be a useful tool for docking and structure-based design.
一种基于每个残基的范德华力(VDW)、静电作用(ES)或氢键(HB)能量的对接重打分方法已被开发出来,以帮助发现与参考物具有相似相互作用特征(足迹)的配体。生物学上有用的参考物可以包括已知药物、抑制剂、底物、过渡态或介导蛋白质 - 蛋白质相互作用的侧链。该方法在程序DOCK中实现,被称为足迹相似性(FPS)评分,通过以下方式进行验证和表征:(1)姿态识别,(2)交叉对接,(3)富集,以及(4)虚拟筛选。在来自SB2010数据库的三个大型数据集(680 - 775个系统)上进行评估时,使用基于足迹的(FPS(VDW + ES))与标准DOCK(DCE(VDW + ES))评分,姿态识别得到了改善(提高了6 - 12%)。与DCE(17.8%)方法相比,使用FPS(45.4%或70.9%)对碳酸酐酶具有挑战性的交叉对接集合进行排序时,也观察到姿态识别得到了增强。对于三个代表性系统的富集测试表明,FPSVDW + ES评分在排名数据库的前10%中产生了显著的早期倍数富集。对于表皮生长因子受体(EGFR),与DCE相比,顶级FPS姿态能很好地容纳在由参考物定义的分子包络中,DCE对较大分子产生明显的分子量偏差。对约100万个化合物进行的代表性虚拟筛选结果进一步说明了如何从大型商业可用数据库中轻松识别出具有与已知抑制剂相似足迹的配体。通过以一种简单而有针对性的方式提供对配体姿态进行排名的替代方法,我们预计FPS评分将成为对接和基于结构设计的有用工具。