Review of multimer protein–protein interaction complex topology and structure prediction?

• 作者: Daiwen Sun Shijie Liu Xinqi Gong
• 来源期刊: 中国物理B（英文版）
• 年，卷（期）: 2020,（10）
• 所属期刊栏目: TOPICAL REVIEW — Modeling and simulations for the structures and functions of proteins and nucleic acids
• 页码范围: 45-55
• 页数: 11页
• 语种: 英文
• DOI: 10.1088/1674-1056/abb659

摘要

Protein–protein interactions (PPI) are important for many biological processes. Theoretical understanding of the structurally determining factors of interaction sites will help to understand the underlying mechanism of protein–protein interactions. At the same time, understanding the complex structure of proteins helps to explore their function. And accurately predicting protein complexes from PPI networks helps us understand the relationship between proteins. In the past few decades, scholars have proposed many methods for predicting protein interactions and protein complex structures. In this review, we first briefly introduce the methods and servers for predicting protein interaction sites and interface residue pairs, and then introduce the protein complex structure prediction methods including template-based prediction and template-free prediction. Subsequently, this paper introduces the methods of predicting protein complexes from the PPI network and the method of predicting missing links in the PPI network. Finally, it briefly summarizes the application of machine/deep learning models in protein structure prediction and action site prediction.