OMPcontact: An Outer Membrane Protein Inter-Barrel Residue Contact Prediction Method

被引:5
作者
Zhang, Li [1 ,4 ]
Wang, Han [2 ]
Yan, Lun [1 ]
Su, Lingtao [1 ]
Xu, Dong [3 ]
机构
[1] Jilin Univ, Sch Comp Sci & Technol, Changchun, Peoples R China
[2] Northeast Normal Univ, Sch Comp Sci & Informat Technol, Changchun, Peoples R China
[3] Univ Missouri, Dept Comp Sci, Christopher S Bond Life Sci Ctr, 201 Engn Bldg West, Columbia, MO 65211 USA
[4] Changchun Univ Technol, Sch Comp Sci & Engn, Changchun, Peoples R China
基金
美国国家卫生研究院; 中国国家自然科学基金;
关键词
contact prediction; evolutionary covariation; outer membrane protein; structure prediction; COUPLED RECEPTORS; TRANSMEMBRANE PROTEINS; SOLVENT ACCESSIBILITY; 3D STRUCTURE; DATA-BANK; IDENTIFICATION; RECOGNITION; GENERATION; TOPOLOGY;
D O I
10.1089/cmb.2015.0236
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
In the two transmembrane protein types, outer membrane proteins (OMPs) perform diverse important biochemical functions, including substrate transport and passive nutrient uptake and intake. Hence their 3D structures are expected to reveal these functions. Because experimental structures are scarce, predicted 3D structures are more adapted to OMP research instead, and the inter-barrel residue contact is becoming one of the most remarkable features, improving prediction accuracy by describing the structural information of OMPs. To predict OMP structures accurately, we explored an OMP inter-barrel residue contact prediction method: OMPcontact. Multiple OMP-specific features were integrated in the method, including residue evolutionary covariation, topology-based transmembrane segment relative residue position, OMP lipid layer accessibility, and residue evolution conservation. These features describe the properties of a residue pair in different respects: sequential, structural, evolutionary, and biochemical. Within a 3-residues slide window, a Support Vector Machine (SVM) could accurately determinate the inter-barrel contact residue pair using above features. A 5-fold cross-valuation process was applied in testing the OMPcontact performance against a non-redundant OMP set with 75 samples inside. The tests compared four evolutionary covariation methods and screen analyzed the adaptive ones for inter-barrel contact prediction. The results showed our method not only efficiently realized the prediction, but also scored the possibility for residue pairs reliably. This is expected to improve OMP tertiary structure prediction. Therefore, OMPcontact will be helpful in compiling a structural census of outer membrane protein.
引用
收藏
页码:217 / 228
页数:12
相关论文
共 51 条
  • [1] Real value prediction of solvent accessibility from amino acid sequence
    Ahmad, S
    Gromiha, MM
    Sarai, A
    [J]. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2003, 50 (04) : 629 - 635
  • [2] Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
    Altschul, SF
    Madden, TL
    Schaffer, AA
    Zhang, JH
    Zhang, Z
    Miller, W
    Lipman, DJ
    [J]. NUCLEIC ACIDS RESEARCH, 1997, 25 (17) : 3389 - 3402
  • [3] The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling
    Arnold, K
    Bordoli, L
    Kopp, J
    Schwede, T
    [J]. BIOINFORMATICS, 2006, 22 (02) : 195 - 201
  • [4] Gene duplication of the eight-stranded β-barrel OmpX produces a functional pore:: A scenario for the evolution of transmembrane β-barrels
    Arnold, Thomas
    Poynor, Melissa
    Nussberger, Stephan
    Lupas, Andrei N.
    Linke, Dirk
    [J]. JOURNAL OF MOLECULAR BIOLOGY, 2007, 366 (04) : 1174 - 1184
  • [5] Correlations among amino acid sites in bHLH protein domains: An information theoretic analysis
    Atchley, WR
    Wollenberg, KR
    Fitch, WM
    Terhalle, W
    Dress, AW
    [J]. MOLECULAR BIOLOGY AND EVOLUTION, 2000, 17 (01) : 164 - 178
  • [6] G protein-coupled receptors:: In silico drug discovery in 3D
    Becker, OM
    Marantz, Y
    Shacham, S
    Inbal, B
    Heifetz, A
    Kalid, O
    Bar-Haim, S
    Warshaviak, D
    Fichman, M
    Noiman, S
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2004, 101 (31) : 11304 - 11309
  • [7] The Protein Data Bank and the challenge of structural genomics
    Berman, HM
    Bhat, TN
    Bourne, PE
    Feng, ZK
    Gilliland, G
    Weissig, H
    Westbrook, J
    [J]. NATURE STRUCTURAL BIOLOGY, 2000, 7 (Suppl 11) : 957 - 959
  • [8] LIBSVM: A Library for Support Vector Machines
    Chang, Chih-Chung
    Lin, Chih-Jen
    [J]. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2011, 2 (03)
  • [9] A machine learning information retrieval approach to protein fold recognition
    Cheng, Jianlin
    Baldi, Pierre
    [J]. BIOINFORMATICS, 2006, 22 (12) : 1456 - 1463
  • [10] From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction
    Cocco, Simona
    Monasson, Remi
    Weigt, Martin
    [J]. PLOS COMPUTATIONAL BIOLOGY, 2013, 9 (08)