Laboratoire Génomique Bioinformatique et Applications, Équipe d'accueil EA 4627, Conservatoire National des Arts et Métiers, 292 rue Saint Martin, 75003 Paris, France.
J Chem Inf Model. 2013 Feb 25;53(2):293-311. doi: 10.1021/ci3004557. Epub 2013 Jan 29.
Structure based virtual ligand screening (SBVLS) methods are widely used in drug discovery programs. When several structures of the target are available, protocols based either on single structure docking or on ensemble docking can be used. The performance of the methods depends on the structure(s) used as a reference, whose choice requires retrospective enrichment studies on benchmarking databases which consume additional resources. In the present study, we have identified several trends in the properties of the binding sites of the structures that led to the optimal performance in retrospective SBVLS tests whatever the docking program used (Surflex-dock or ICM). By assessing their hydrophobicity and comparing their volume and opening, we show that the selection of optimal structures should be possible with no requirement of prior retrospective enrichment studies. If the mean binding site volume is lower than 350 A(3), the structure with the smaller volume should be preferred. In the other cases, the structure with the largest binding site should be preferred. These optimal structures may be either selected for a single structure docking strategy or an ensemble docking strategy. When constructing an ensemble, the opening of the site might be an interesting criterion additionaly to its volume as the most closed structures should not be preferred in the large systems. These "binding site properties-based" guidelines could be helpful to optimize future prospective drug discovery protocols when several structures of the target are available.
基于结构的虚拟配体筛选（SBVLS）方法在药物发现计划中被广泛应用。当有多个目标结构可用时，可以使用基于单个结构对接或整体对接的协议。这些方法的性能取决于用作参考的结构，选择参考结构需要对基准数据库进行回顾性富集研究，这会消耗额外的资源。在本研究中，我们已经确定了几个与结合部位特性相关的趋势，这些趋势导致了无论使用哪种对接程序（Surflex-dock 或 ICM），在回顾性 SBVLS 测试中的最佳性能。通过评估它们的疏水性，并比较它们的体积和开口度，我们表明无需进行先前的回顾性富集研究即可选择最佳结构。如果平均结合部位体积小于 350A(3)，则应选择体积较小的结构。在其他情况下，应选择具有最大结合部位的结构。这些最佳结构可以用于单个结构对接策略或整体对接策略。在构建整体结构时，除了体积之外，结合部位的开口度也可能是一个有趣的标准，因为在大型系统中，不应选择最封闭的结构。这些“基于结合部位特性”的指南可以帮助优化未来具有多个目标结构的药物发现方案。
