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序列共同进化赋予蛋白质复合物三维接触和结构。

Sequence co-evolution gives 3D contacts and structures of protein complexes.

作者信息

Hopf Thomas A, Schärfe Charlotta P I, Rodrigues João P G L M, Green Anna G, Kohlbacher Oliver, Sander Chris, Bonvin Alexandre M J J, Marks Debora S

机构信息

Department of Systems Biology, Harvard University, Boston, United States.

Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, Netherlands.

出版信息

Elife. 2014 Sep 25;3:e03430. doi: 10.7554/eLife.03430.

DOI:10.7554/eLife.03430
PMID:25255213
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4360534/
Abstract

Protein-protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein-protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein-protein interaction networks and used for interaction predictions at residue resolution.

摘要

蛋白质-蛋白质相互作用是许多生物过程的基础。实验筛选已鉴定出数以万计的相互作用,结构生物学也为选定的三维蛋白质复合物提供了详细的功能见解。关于蛋白质相互作用的另一个丰富信息来源是进化序列记录。基于早期的工作,我们表明,对蛋白质间相关进化序列变化的分析能够以足够的准确性识别出在空间上接近的残基,从而确定蛋白质复合物的三维结构。我们在对76个已知三维结构的复合物进行的盲测中评估了预测性能,预测了32个未知结构复合物中的蛋白质-蛋白质接触,并展示了进化偶联如何用于区分大型复合物中相互作用和非相互作用的蛋白质对。随着当前序列数量的增长,我们预计该方法可以推广到全基因组范围的蛋白质-蛋白质相互作用网络解析,并用于残基分辨率下的相互作用预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/79685743485b/elife03430f007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/79685743485b/elife03430f007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/c7719eed29a4/elife03430f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/e0b68aa43741/elife03430fs001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/cf8ee6bf6202/elife03430fs009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/24d9812f06af/elife03430f003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/36c585c3ac9e/elife03430f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/ff43e15e897a/elife03430f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/49bb92905180/elife03430fs011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/814409689d39/elife03430fs012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/6945055358f7/elife03430fs013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/f44683afa265/elife03430f006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/e07e9a006177/elife03430fs014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/061e/4360534/79685743485b/elife03430f007.jpg

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