Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, New York 11794, USA.
Institute of Chemical Biology & Drug Discovery, Stony Brook University, Stony Brook, New York 11794, USA.
J Comput Chem. 2013 May 30;34(14):1226-1240. doi: 10.1002/jcc.23245. Epub 2013 Feb 22.
Scoring functions are a critically important component of computer-aided screening methods for the identification of lead compounds during early stages of drug discovery. Here, we present a new multigrid implementation of the footprint similarity (FPS) scoring function that was recently developed in our laboratory which has proven useful for identification of compounds which bind to a protein on a per-residue basis in a way that resembles a known reference. The grid-based FPS method is much faster than its Cartesian-space counterpart, which makes it computationally tractable for on-the-fly docking, virtual screening, or de novo design. In this work, we establish that: (i) relatively few grids can be used to accurately approximate Cartesian space footprint similarity, (ii) the method yields improved success over the standard DOCK energy function for pose identification across a large test set of experimental co-crystal structures, for crossdocking, and for database enrichment, and (iii) grid-based FPS scoring can be used to tailor construction of new molecules to have specific properties, as demonstrated in a series of test cases targeting the viral protein HIVgp41. The method is available in the program DOCK6.
评分函数是计算机辅助筛选方法在药物发现早期识别先导化合物的关键组成部分。在这里,我们提出了一种新的足迹相似性 (FPS) 评分函数的多重网格实现,该函数是我们实验室最近开发的,已被证明对识别以类似于已知参考的方式结合到蛋白质上的化合物很有用。基于网格的 FPS 方法比其笛卡尔空间对应方法快得多,这使得它在即时对接、虚拟筛选或从头设计方面具有计算可行性。在这项工作中,我们确定:(i) 可以使用相对较少的网格来准确逼近笛卡尔空间足迹相似性,(ii) 该方法在大型实验共晶结构测试集、交叉对接和数据库富集的构象识别方面的成功率高于标准 DOCK 能量函数,(iii) 基于网格的 FPS 评分可用于定制新分子的构建以具有特定性质,如针对病毒蛋白 HIVgp41 的一系列测试案例所示。该方法可在程序 DOCK6 中使用。