Robust and accurate prediction of residue-residue interactions across protein interfaces using evolutionary information

被引:462
|
作者
Ovchinnikov, Sergey [1 ,2 ,3 ]
Kamisetty, Hetunandan [1 ,2 ,4 ]
Baker, David [1 ,2 ]
机构
[1] Univ Washington, Howard Hughes Med Inst, Seattle, WA 98195 USA
[2] Univ Washington, Dept Biochem, Seattle, WA 98195 USA
[3] Univ Washington, Mol & Cellular Biol Program, Seattle, WA 98195 USA
[4] Facebook Inc, Seattle, WA 98101 USA
来源
ELIFE | 2014年 / 3卷
关键词
PYRUVATE FORMATE-LYASE; CRYSTAL-STRUCTURE; STRUCTURAL BASIS; CONTACT PREDICTION; WEB SERVER; SEQUENCE; FAMILIES; RESOLUTION; CONFORMATIONS; COEVOLUTION;
D O I
10.7554/eLife.02030
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Do the amino acid sequence identities of residues that make contact across protein interfaces covary during evolution? If so, such covariance could be used to predict contacts across interfaces and assemble models of biological complexes. We find that residue pairs identified using a pseudolikelihood based method to covary across protein-protein interfaces in the 50S ribosomal unit and 28 additional bacterial protein complexes with known structure are almost always in contact in the complex provided that the number of aligned sequences is greater than the average of the lengths of the two proteins. We use this method to make subunit contact predictions for an additional 36 protein complexes with unknown structures, and present models based on these predictions for the tripartite ATP-independent periplasmic (TRAP) transporter, the tripartite efflux system, the pyruvate formate lyase-activating enzyme complex, and the methionine ABC transporter.!
引用
收藏
页数:25
相关论文
共 50 条
  • [21] COMTOP: Protein Residue-Residue Contact Prediction through Mixed Integer Linear Optimization
    Reza, Md Selim
    Zhang, Huiling
    Hossain, Md Tofazzal
    Jin, Langxi
    Feng, Shengzhong
    Wei, Yanjie
    MEMBRANES, 2021, 11 (07)
  • [22] Predicting protein residue-residue contacts using random forests and deep networks
    Joseph Luttrell
    Tong Liu
    Chaoyang Zhang
    Zheng Wang
    BMC Bioinformatics, 20
  • [23] IMPROVING RESIDUE-RESIDUE CONTACTS PREDICTION FROM PROTEIN SEQUENCES USING RNN-BASED LSTM NETWORK
    Chen, Wenjing
    Sun, Jianfeng
    Gao, Chunhui
    PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), 2019, : 601 - 607
  • [24] Predicting protein residue-residue contacts using random forests and deep networks
    Luttrell, Joseph
    Liu, Tong
    Zhang, Chaoyang
    Wang, Zheng
    BMC BIOINFORMATICS, 2019, 20 (Suppl 2)
  • [25] DeepRCI: Predicting ATP-Binding Proteins Using the Residue-Residue Contact Information
    Zhang, Zhaoxi
    Zhao, Yulan
    Wang, Juan
    Guo, Maozu
    IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2022, 26 (06) : 2822 - 2829
  • [26] A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information
    Yi, Hai-Cheng
    You, Zhu-Hong
    Huang, De-Shuang
    Li, Xiao
    Jiang, Tong-Hai
    Li, Li-Ping
    MOLECULAR THERAPY-NUCLEIC ACIDS, 2018, 11 : 337 - 344
  • [27] CCMpred-fast and precise prediction of protein residue-residue contacts from correlated mutations
    Seemayer, Stefan
    Gruber, Markus
    Soeding, Johannes
    BIOINFORMATICS, 2014, 30 (21) : 3128 - 3130
  • [28] Prediction of residue-residue contact matrix for protein-protein interaction with Fisher score features and deep learning
    Du, Tianchuan
    Liao, Li
    Wu, Cathy H.
    Sun, Bilin
    METHODS, 2016, 110 : 97 - 105
  • [29] Robust and accurate prediction of protein self-interactions from amino acids sequence using evolutionary information
    An, Ji-Yong
    You, Zhu-Hong
    Chen, Xing
    Huang, De-Shuang
    Yan, Guiying
    Wang, Da-Fu
    MOLECULAR BIOSYSTEMS, 2016, 12 (12) : 3702 - 3710
  • [30] An interpretable machine learning method for homo-trimeric protein interface residue-residue interaction prediction
    Hong, Zhonghua
    Liu, Jiale
    Chen, Yinggao
    BIOPHYSICAL CHEMISTRY, 2021, 278