Decoding Protein-protein Interactions: An Overview

被引:11
|
作者
Slater, Olivia [1 ]
Miller, Bethany [1 ]
Kontoyianni, Maria [1 ]
机构
[1] Southern Illinois Univ, Dept Pharmaceut Sci, Edwardsville, IL 62026 USA
关键词
Protein-protein interactions; protein-protein interface; disease networks; hot spots; molecular recognition; protein-protein docking; machine learning methods; binding site identification; BINDING SITE PREDICTION; WEB SERVER; HOT-SPOTS; SMALL-MOLECULE; SHAPE COMPLEMENTARITY; INTERACTION NETWORKS; BOOSTING PREDICTION; INTERFACE RESIDUES; CRYSTAL-STRUCTURE; FUNCTIONAL SITES;
D O I
10.2174/1568026620666200226105312
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Drug discovery has focused on the paradigm "one drug, one target" for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.
引用
收藏
页码:855 / 882
页数:28
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