Department of Bio and Brain Engineering, KAIST, Daejeon 34141, Republic of Korea.
Bioinformatics. 2020 Feb 1;36(3):959-960. doi: 10.1093/bioinformatics/btz656.
Identification of putative drug targets is a critical step for explaining the mechanism of drug action against multiple targets, finding new therapeutic indications for existing drugs and unveiling the adverse drug reactions. One important approach is to use the molecular docking. However, its widespread utilization has been hindered by the lack of easy-to-use public servers. Therefore, it is vital to develop a streamlined computational tool for target prediction by molecular docking on a large scale.
We present a fully automated web tool named Consensus Reverse Docking System (CRDS), which predicts potential interaction sites for a given drug. To improve hit rates, we developed a strategy of consensus scoring. CRDS carries out reverse docking against 5254 candidate protein structures using three different scoring functions (GoldScore, Vina and LeDock from GOLD version 5.7.1, AutoDock Vina version 1.1.2 and LeDock version 1.0, respectively), and those scores are combined into a single score named Consensus Docking Score (CDS). The web server provides the list of top 50 predicted interaction sites, docking conformations, 10 most significant pathways and the distribution of consensus scores.
The web server is available at http://pbil.kaist.ac.kr/CRDS.
Supplementary data are available at Bioinformatics online.
鉴定潜在的药物靶点对于解释药物针对多个靶点的作用机制、为现有药物寻找新的治疗适应症以及揭示药物不良反应至关重要。一种重要的方法是使用分子对接。然而，由于缺乏易于使用的公共服务器，其广泛应用受到了阻碍。因此，开发一种用于大规模分子对接的目标预测的流线型计算工具是至关重要的。
我们提出了一个名为共识反向对接系统（CRDS）的全自动网络工具，该工具可预测给定药物的潜在相互作用位点。为了提高命中率，我们开发了一种共识评分策略。CRDS 使用三种不同的评分函数（来自 GOLD 版本 5.7.1 的 GoldScore、Vina 和 LeDock、AutoDock Vina 版本 1.1.2 和 LeDock 版本 1.0）对 5254 个候选蛋白结构进行反向对接，并将这些得分组合成一个名为共识对接得分（CDS）的单一得分。该网络服务器提供了前 50 个预测相互作用位点、对接构象、10 个最重要的途径以及共识得分分布的列表。
该网络服务器可在 http://pbil.kaist.ac.kr/CRDS 上使用。
补充数据可在 Bioinformatics 在线获得。
