DiffBond: A Method for Predicting Intermolecular Bond Formation.

DiffBond: A Method for Predicting Intermolecular Bond Formation.
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DOI:
10.1109/bibm52615.2021.9669850
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发表时间:
2021-12
期刊:
Proceedings. IEEE International Conference on Bioinformatics and Biomedicine
影响因子:
--
通讯作者:
Chen BY
Chen BY
中科院分区:
其他
文献类型:
--
作者:
Tam J;Palumbo T;Miwa JM;Chen BY

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许多探索蛋白质复合体模型的工具也能够分析特定残基与原子之间的相互作用。对这些相互作用的全面探索通常可以发现蛋白质-蛋白质识别的一些方面,而这些方面使用其他蛋白质分析技术并不明显。本文描述了DiffBond,这是一种新的方法,用于研究蛋白质复合体之间的分子间相互作用,同时区分三种不同类型的相互作用:氢键、离子键和盐桥。DiffBond结合了教科书上对这三种相互作用的定义,同时与相互作用蛋白质的计算模型中固有的不确定性作了斗争。我们用它来研究Barnase-Barstar、Rap1a-RAF和Smad2-Smad4复合体,以及三指毒素和nAChRs之间形成的蛋白质复合体的子集。基于先前实验研究建立的静电相互作用,DiffBond能够高精度和召回性地识别离子和氢键,并高精度地识别盐桥。与其他静电分析方法相结合,DiffBond可以成为帮助预测蛋白质-蛋白质相互作用中有影响的氨基酸和表征相互作用类型的有用工具。
Many tools that explore models of protein complexes are also able to analyze interactions between specific residues and atoms. A comprehensive exploration of these interactions can often uncover aspects of protein-protein recognition that are not obvious using other protein analysis techniques. This paper describes DiffBond, a novel method for searching for intermolecular interactions between protein complexes while differentiating between three different types of interaction: hydrogen bonds, ionic bonds, and salt bridges. DiffBond incorporates textbook definitions of these three interactions while contending with uncertainties that are inherent in computational models of interacting proteins. We used it to examine the barnase-barstar, Rap1a-raf, and Smad2-Smad4 complexes, as well as a subset of protein complexes formed between three-finger toxins and nAChRs. Based on electrostatic interactions established by previous experimental studies, DiffBond was able to identify ionic and hydrogen bonds with high precision and recall, and identify salt bridges with high precision. In combination with other electrostatic analysis methods, DiffBond can be a useful tool in helping predict influential amino acids in protein-protein interactions and characterizing the type of interaction.