计算机科学
蛋白质-蛋白质相互作用
蛋白质相互作用网络
基础(线性代数)
计算生物学
数据挖掘
生物
数学
几何学
遗传学
作者
Christina Kiel,Pedro Beltrão,Luís Serrano
标识
DOI:10.1146/annurev.biochem.77.062706.133317
摘要
Determining protein interaction networks and predicting network changes in time and space are crucial to understanding and modeling a biological system. In the past few years, the combination of experimental and computational tools has allowed great progress toward reaching this goal. Experimental methods include the large-scale determination of protein interactions using two-hybrid or pull-down analysis as well as proteomics. The latter one is especially valuable when changes in protein concentrations over time are recorded. Computational tools include methods to predict and validate protein interactions on the basis of structural information and bioinformatics tools that analyze and integrate data for the same purpose. In this review, we focus on the use of structural information in combination with computational tools to predict new protein interactions, to determine which interactions are compatible with each other, to obtain some functional insight into single and multiple mutations, and to estimate equilibrium and kinetic parameters. Finally, we discuss the importance of establishing criteria to biologically validate protein interactions.
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