Depicting a ligand-receptor complex via Interaction Fingerprints has been shown to be both a viable data visualization and an analysis tool. The spectrum of its applications ranges from simple visualization of the binding site through analysis of molecular dynamics runs, to the evaluation of the homology models and virtual screening. Here we present a novel tool derived from the Structural Interaction Fingerprints providing a detailed and unique insight into the interactions between receptor and specific regions of the ligand (grouped into pharmacophore features) in the form of a matrix, a 2D-SIFt descriptor. The provided implementation is easy to use and extends the python library, allowing the generation of interaction matrices and their manipulation (reading and writing as well as producing the average 2D-SIFt). The library for handling the interaction matrices is available via repository http://bitbucket.org/zchl/sift2d .

中文翻译：

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2D SIFt：配体-受体相互作用矩阵

通过交互指纹描绘配体-受体复合物已被证明是一种可行的数据可视化和分析工具。其应用范围从结合位点的简单可视化到分子动力学运行的分析，到同源性模型的评估和虚拟筛选。在这里，我们提出了一种源自结构相互作用指纹的新工具，以矩阵的形式提供了对受体与配体特定区域（分组为药效团特征）之间相互作用的详细而独特的见解，这是一种 2D-SIFt 描述符。提供的实现易于使用并扩展了 python 库，允许生成交互矩阵及其操作（读取和写入以及生成平均 2D-SIFt）。