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首页> 外文期刊>Journal of Computational Chemistry: Organic, Inorganic, Physical, Biological >Pattern Recognition Strategies for Molecular Surfaces:III.Binding Site Prediction with a Neural Network
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Pattern Recognition Strategies for Molecular Surfaces:III.Binding Site Prediction with a Neural Network

机译:分子表面的模式识别策略:III。神经网络的结合位点预测

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摘要

An algorithm for the identification of possible binding sites of biomolecules,which are represented as regions of the molecular surface,is introduced.The algorithm is based on the segmentation of the molecular surface into overlapping patches as described in the first article of this series.The properties of these patches (calculated on the basis of physical and chemical properties) are used for the analysis of the molecular surfaces of 7821 proteins and protein complexes.Special attention is drawn to known protein binding sites.A binding site identification algorithm is realized on the basis of the calculated data using a neural network strategy.The neural network is able to classify surface patches as protein-protein,protein-DNA,protein-ligand,or nonbinding sites.To show the capability of the algorithm,results of the surface analysis and the predictions are presented and discussed with representative examples.
机译:引入了一种识别可能存在的生物分子结合位点的算法,以分子表面的区域表示。该算法基于分子表面分割成重叠斑块的方法,如本系列第一篇文章所述。这些补丁的性质(根据物理和化学性质计算)用于分析7821蛋白质和蛋白质复合物的分子表面。特别注意已知的蛋白质结合位点。利用神经网络策略计算数据的基础。神经网络能够将表面斑块分类为蛋白质-蛋白质,蛋白质-DNA,蛋白质-配体或非结合位点。为了显示算法的功能,表面分析的结果并通过代表性示例介绍和讨论了预测。

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