rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acids

Identification of chemical compounds with specific biological activities is an important step in both chemical biology and drug discovery. When the structure of the intended target is available, one approach is to use molecular docking programs to assess the chemical complementarity of small molecules with the target; such calculations provide a qualitative measure of affinity that can be used in virtual screening (VS) to rank order a list of compounds according to their potential to be active. rDock is a molecular docking program developed at Vernalis for high-throughput VS (HTVS) applications. Evolved from RiboDock, the program can be used against proteins and nucleic acids, is designed to be computationally very efficient and allows the user to incorporate additional constraints and information as a bias to guide docking. This article provides an overview of the program structure and features and compares rDock to two reference programs, AutoDock Vina (open source) and Schrödinger's Glide (commercial). In terms of computational speed for VS, rDock is faster than Vina and comparable to Glide. For binding mode prediction, rDock and Vina are superior to Glide. The VS performance of rDock is significantly better than Vina, but inferior to Glide for most systems unless pharmacophore constraints are used; in that case rDock and Glide are of equal performance. The program is released under the Lesser General Public License and is freely available for download, together with the manuals, example files and the complete test sets, at http://rdock.sourceforge.net/

筛选具有特定生物活性的化合物，是化学生物学与药物发现领域的核心环节。当目标靶点的三维结构已知时，可借助分子对接程序评估小分子与靶点的化学互补性；此类计算可得到亲和力的定性表征，用于虚拟筛选（Virtual Screening, VS），进而依据化合物的潜在活性对其进行排序。rDock是Vernalis公司开发的一款面向高通量虚拟筛选（high-throughput VS, HTVS）的分子对接程序。该程序脱胎于RiboDock，可针对蛋白质与核酸靶点进行对接，具备极高的计算效率，且支持用户引入额外约束条件与信息作为引导对接的偏置项。本文概述了该程序的结构与特性，并将rDock与两款参考程序——开源的AutoDock Vina以及商用的Schrödinger's Glide——进行了对比。在虚拟筛选的计算速度方面，rDock的运算速度快于Vina，且与Glide相当。在结合模式预测性能上，rDock与Vina均优于Glide。rDock的虚拟筛选性能显著优于Vina，但在多数体系中略逊于Glide，除非引入药效团约束；此时rDock与Glide的性能不相上下。本程序以宽通用公共许可证（Lesser General Public License）发布，用户可通过http://rdock.sourceforge.net/免费下载获取，同时可获得配套手册、示例文件与完整测试数据集。