ComplexContact: a web server for inter-protein contact prediction using deep learning

被引:95
作者
Zeng, Hong [1 ]
Wang, Sheng [2 ,3 ]
Zhou, Tianming [3 ,4 ]
Zhao, Feifeng [1 ]
Li, Xiufeng [1 ]
Wu, Qing [1 ]
Xu, Jinbo [3 ]
机构
[1] Hangzhou Dianzi Univ, Sch Comp Sci & Technol, Hangzhou, Zhejiang, Peoples R China
[2] King Abdullah Univ Sci & Technol, Thuwal, Saudi Arabia
[3] Toyota Technol Inst Chicago, Chicago, IL 60637 USA
[4] Tsinghua Univ, Inst Interdisciplinary Informat Sci, Beijing, Peoples R China
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
COUPLING ANALYSIS; RESIDUE CONTACTS; COEVOLUTION; SEQUENCE; IDENTIFICATION;
D O I
10.1093/nar/gky420
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequencebased interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.
引用
收藏
页码:W432 / W437
页数:6
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