蛋白质结合界面中相互作用残基构象稳定性的分析。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Varun M Chauhan, Robert J Pantazes
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引用次数: 0

摘要

经过大约60年的工作,由于AlphaFold和RoseTTAFold的发明,蛋白质折叠问题最近得到了快速发展,这两种机器学习算法能够根据其序列可靠地预测蛋白质结构。他们成功的一个关键因素是包含了残基之间的成对相互作用信息。随着研究重点转向开发设计和工程结合蛋白的算法,蛋白质界面相互作用特征的知识很可能可以改进预测。在此,分析了574种蛋白质复合物,以确定其成对相互作用的稳定性特征,揭示了预稳定残基之间的相互作用是蛋白质结合界面中的一个选定特征。在475种新设计的结合蛋白的回顾性分析中,实验成功率为19%,包含成对相互作用预稳定参数将鉴定实验成功结合蛋白的频率提高到40%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of conformational stability of interacting residues in protein binding interfaces.

After approximately 60 years of work, the protein folding problem has recently seen rapid advancement thanks to the inventions of AlphaFold and RoseTTAFold, which are machine-learning algorithms capable of reliably predicting protein structures from their sequences. A key component in their success was the inclusion of pairwise interaction information between residues. As research focus shifts towards developing algorithms to design and engineer binding proteins, it is likely that knowledge of interaction features at protein interfaces can improve predictions. Here, 574 protein complexes were analyzed to identify the stability features of their pairwise interactions, revealing that interactions between pre-stabilized residues are a selected feature in protein binding interfaces. In a retrospective analysis of 475 de novo designed binding proteins with an experimental success rate of 19%, inclusion of pairwise interaction pre-stabilization parameters increased the frequency of identifying experimentally successful binders to 40%.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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