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A fast topological analysis algorithm for large-scale similarity evaluations of ligands and binding pockets

机译:用于配体和结合口袋大规模相似性评估的快速拓扑分析算法

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摘要

Motivation: With the rapid increase of the structural data of biomolecular complexes, novel structural analysis methods have to be devised with high-throughput capacity to handle immense data input and to construct massive networks at the minimal computational cost. Moreover, novel methods should be capable of handling a broad range of molecular structural sizes and chemical natures, cognisant of the conformational and electrostatic bases of molecu- lar recognition, and sufficiently accurate to enable contextually relevant biological inferences.Results: A novel molecular topology comparison method was developed and tested. The method was tested for both ligand and binding pocket similarity analyses and a PDB-wide ligand topological similarity map was computed.Conclusion: The unprecedentedly wide scope of ligand definition and large-scale topological similarity mapping can provide very robust tools, of performance unmatched by the present alignment-based methods. The method remarkably shows potential for application for scaffold hopping purposes. It also opens new frontiers in the areas of ligand-mediated protein connectivity, ligand-based molecular phylogeny, target fishing, and off-target predictions.
机译:动机:随着生物分子复合物结构数据的迅速增加,必须设计出具有高通量能力的新颖结构分析方法,以处理巨大的数据输入并以最小的计算成本构建庞大的网络。此外,新颖的方法应该能够处理广泛的分子结构尺寸和化学性质,能够识别分子识别的构象和静电碱基,并且具有足够的准确度以支持与上下文相关的生物学推断。结果:新颖的分子拓扑比较方法被开发和测试。测试了该方法的配体和结合口袋相似性分析,并计算了PDB范围的配体拓扑相似性图。结论:前所未有的宽范围的配体定义和大规模拓扑相似性映射可以提供非常强大的工具,其性能无法与当前基于比对的方法。该方法显着显示了用于支架跳跃目的的潜力。它还在配体介导的蛋白质连通性,基于配体的分子系统发育,目标捕捞和脱靶预测领域开辟了新领域。

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