Prediction of Protein-Protein Interface Sequence Diversity Using Flexible Backbone Computational Protein Design

被引:65
|
作者
Humphris, Elisabeth L. [1 ,2 ]
Kortemme, Tanja [1 ,2 ,3 ]
机构
[1] Univ Calif San Francisco, Grad Grp Biophys, San Francisco, CA 94158 USA
[2] Univ Calif San Francisco, Calif Inst Quantitat Biosci, San Francisco, CA 94158 USA
[3] Univ Calif San Francisco, Dept Biopharmaceut Sci, San Francisco, CA 94158 USA
关键词
D O I
10.1016/j.str.2008.09.012
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
A major challenge in computational protein design is to identify functional sequences as top predictions. One reason for design failures is conformational plasticity, as proteins frequently change their conformation in response to mutations. To advance protein design, here we describe a method employing flexible backbone ensembles to predict sequences tolerated for a protein-protein interface. We show that the predictions are enriched in functional proteins when compared to a phage display screen quantitatively mapping the energy landscape for the interaction between human growth hormone and its receptor. Our model for structural plasticity is inspired by coupled side chain-backbone "backrub" motions observed in high-resolution protein crystal structures. Although the modeled structural changes are subtle, our results on predicting sequence plasticity suggest that backrub sampling may capture a sizable fraction of localized conformational changes that occur in proteins. The described method has implications for predicting sequence libraries to enable challenging protein engineering problems.
引用
收藏
页码:1777 / 1788
页数:12
相关论文
共 50 条
  • [1] Increasing Sequence Diversity with Flexible Backbone Protein Design: The Complete Redesign of a Protein Hydrophobic Core
    Murphy, Grant S.
    Mills, Jeffrey L.
    Miley, Michael J.
    Machius, Mischa
    Szyperski, Thomas
    Kuhlman, Brian
    STRUCTURE, 2012, 20 (06) : 1086 - 1096
  • [2] Prediction of protein-protein interface residues using sequence neighborhood and surface properties
    Arafat, Yasir
    Kamruzzaman, Joarder
    Karmakar, Gour
    ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS, 2006, 3973 : 660 - 666
  • [3] Protein docking prediction using predicted protein-protein interface
    Bin Li
    Daisuke Kihara
    BMC Bioinformatics, 13
  • [4] Protein docking prediction using predicted protein-protein interface
    Li, Bin
    Kihara, Daisuke
    BMC BIOINFORMATICS, 2012, 13
  • [5] Using Designability to Design a Protein-Protein Interface
    Hannigan, Brett
    Schramm, Chaim
    Gonzalez, Gabriel
    DeGrado, William
    PROTEIN SCIENCE, 2012, 21 : 133 - 133
  • [6] Prediction of protein-protein binding affinity using diverse protein-protein interface features
    Ma, Duo
    Guo, Yanzhi
    Luo, Jiesi
    Pu, Xuemei
    Li, Menglong
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2014, 138 : 7 - 13
  • [8] Prediction of protein-protein binding affinity using diverse protein-protein interface features
    Ma, Duo
    Guo, Yanzhi
    Luo, Jiesi
    Pu, Xuemei
    Li, Menglong
    Chemometrics and Intelligent Laboratory Systems, 2014, 138 : 7 - 13
  • [9] Conformer selection and induced fit in flexible backbone protein-protein docking using computational and NMR ensembles
    Chaudhury, Sidhartha
    Gray, Jeffrey J.
    JOURNAL OF MOLECULAR BIOLOGY, 2008, 381 (04) : 1068 - 1087
  • [10] Computational prediction of protein-protein interactions
    Skrabanek, Lucy
    Saini, Harpreet K.
    Bader, Gary D.
    Enright, Anton J.
    MOLECULAR BIOTECHNOLOGY, 2008, 38 (01) : 1 - 17