Laboratory of Therapeutic Innovation, UMR 7200 Université de Strasbourg/CNRS, Medalis Drug Discovery Center, F-67400 Illkirch, France.
J Chem Inf Model. 2012 Aug 27;52(8):2287-99. doi: 10.1021/ci300184x. Epub 2012 Aug 16.
Estimating the pairwise similarity of protein-ligand binding sites is a fast and efficient way of predicting cross-reactivity and putative side effects of drug candidates. Among the many tools available, three-dimensional (3D) alignment-dependent methods are usually slow and based on simplified representations of binding site atoms or surfaces. On the other hand, fast and efficient alignment-free methods have recently been described but suffer from a lack of interpretability. We herewith present a novel binding site description (VolSite), coupled to an alignment and comparison tool (Shaper) combining the speed of alignment-free methods with the interpretability of alignment-dependent approaches. It is based on the comparison of negative images of binding cavities encoding both shape and pharmacophoric properties at regularly spaced grid points. Shaper approximates the resulting molecular shape with a smooth Gaussian function and aligns protein binding sites by optimizing their volume overlap. Volsite and Shaper were successfully applied to compare protein-ligand binding sites and to predict their structural druggability.
估算蛋白质-配体结合位点的两两相似性是预测药物候选物交叉反应性和潜在副作用的一种快速有效的方法。在众多可用的工具中，三维（3D）依赖于对齐的方法通常较慢，并且基于结合位点原子或表面的简化表示。另一方面，最近已经描述了快速有效的无对齐方法，但缺乏可解释性。我们在此提出了一种新的结合位点描述（VolSite），并结合了一种对齐和比较工具（Shaper），该工具将无对齐方法的速度与依赖于对齐的方法的可解释性相结合。它基于在规则间隔的网格点处编码形状和药效团特性的结合腔负像的比较。Shaper 使用平滑的高斯函数来近似得到的分子形状，并通过优化它们的体积重叠来对齐蛋白质结合位点。Volsite 和 Shaper 成功地应用于比较蛋白质-配体结合位点，并预测它们的结构可成药性。
