Mordalski Stefan, Wojtuch Agnieszka, Podolak Igor, Kurczab Rafał, Bojarski Andrzej J
Department of Medicinal Chemistry, Maj Institute of Pharmacology Polish Academy of Sciences, Krakow, Poland.
Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland.
J Cheminform. 2021 Sep 8;13(1):66. doi: 10.1186/s13321-021-00545-9.
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 .
通过相互作用指纹图谱描绘配体-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。其应用范围从通过分子动力学模拟分析简单可视化结合位点，到同源性模型评估和虚拟筛选。在这里，我们展示了一种源自结构相互作用指纹图谱的新型工具，它以矩阵（二维SIFt描述符）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且独特的见解。所提供的实现易于使用，并扩展了Python库，允许生成相互作用矩阵并对其进行操作（读取、写入以及生成平均二维SIFt）。用于处理相互作用矩阵的库可通过存储库http://bitbucket.org/zchl/sift2d获取。
