成对比较
理论(学习稳定性)
计算机科学
蛋白质-蛋白质相互作用
蛋白质折叠
折叠(DSP实现)
光学(聚焦)
蛋白质工程
化学
特征(语言学)
计算生物学
血浆蛋白结合
生物系统
结晶学
人工智能
机器学习
生物化学
生物
工程类
酶
物理
哲学
光学
电气工程
语言学
作者
Varun M. Chauhan,Robert J. Pantazes
出处
期刊:Protein Engineering Design & Selection
[Oxford University Press]
日期:2023-10-27
标识
DOI:10.1093/protein/gzad016
摘要
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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