Protein Interface Residues Prediction Based on Amino Acid Properties Only

被引:0
作者
Wang, Bing [1 ,2 ]
Chen, Peng [3 ]
Zhang, Jun [2 ]
机构
[1] Anhui Univ Technol, Sch Elect Engn & Informat, Maanshan 243002, Anhui, Peoples R China
[2] Univ Louisville, Dept Chem, Louisville, KY 40292 USA
[3] Chinese Acad Sci, Hefei Inst Intelligent Machines, Hefei 230031, Peoples R China
来源
BIO-INSPIRED COMPUTING AND APPLICATIONS | 2012年 / 6840卷
基金
美国国家科学基金会;
关键词
Amino Acid Property; Protein Interface Residues; Support Vector Machines; Hetero-complexes; INTERACTION SITES;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Protein-protein interactions play essential roles in protein function implementation. A computational model is introduced in this work for predicting protein interface residues based on amino acid chemicophysical properties only. 17 amino acid properties are selected from AAindex database and used as input features of a prediction model which is constructed by support vector machines method to infer protein interface residues in protein hetero-complexes. The results achieved in this work demonstrated the properties used in this work can actually capture up the difference between interface and noninterface residues.
引用
收藏
页码:448 / +
页数:2
相关论文
共 50 条
  • [31] DNA binding protein identification by combining pseudo amino acid composition and profile-based protein representation
    Liu, Bin
    Wang, Shanyi
    Wang, Xiaolong
    SCIENTIFIC REPORTS, 2015, 5
  • [32] Robust prediction of mutation-induced protein stability change by property encoding of amino acids
    Kang, Shuli
    Chen, Gang
    Xiao, Gengfu
    PROTEIN ENGINEERING DESIGN & SELECTION, 2009, 22 (02) : 75 - 83
  • [33] Important amino acid properties for determining the transition state structures of two-state protein mutants
    Gromiha, MM
    Selvaraj, S
    FEBS LETTERS, 2002, 526 (1-3) : 129 - 134
  • [34] Prediction of nuclear receptors with optimal pseudo amino acid composition
    Gao, Qing-Bin
    Jin, Zhi-Chao
    Ye, Xiao-Fei
    Wu, Cheng
    He, Jia
    ANALYTICAL BIOCHEMISTRY, 2009, 387 (01) : 54 - 59
  • [35] Prediction of G-protein-coupled receptor classes based on the concept of Chou's pseudo amino acid composition: An approach from discrete wavelet transform
    Qiu, Jian-Ding
    Huang, Jian-Hua
    Liang, Ru-Ping
    Lu, Xiao-Quan
    ANALYTICAL BIOCHEMISTRY, 2009, 390 (01) : 68 - 73
  • [36] Classification and prediction of protein-protein interaction interface using machine learning algorithm
    Das, Subhrangshu
    Chakrabarti, Saikat
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [37] Using pseudo amino acid composition to predict protein subcellular location: approached with amino acid composition distribution
    Shi, J. -Y.
    Zhang, S. -W.
    Pan, Q.
    Zhou, G. -P.
    AMINO ACIDS, 2008, 35 (02) : 321 - 327
  • [38] Predicting protein-protein interactions by weighted pseudo amino acid composition
    Goktepe, Yunus Emre
    Ilhan, Ilhan
    Kahramanli, Sirzat
    INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS, 2016, 15 (03) : 272 - 290
  • [39] Protein Remote Homology Detection by Combining Chou's Pseudo Amino Acid Composition and Profile-Based Protein Representation
    Liu, Bin
    Wang, Xiaolong
    Zou, Quan
    Dong, Qiwen
    Chen, Qingcai
    MOLECULAR INFORMATICS, 2013, 32 (9-10) : 775 - 782
  • [40] Prediction of GPCRs with Pseudo Amino Acid Composition: Employing Composite Features and Grey Incidence Degree Based Classification
    Zia-ur-Rehman
    Khan, Asifullah
    PROTEIN AND PEPTIDE LETTERS, 2011, 18 (09) : 872 - 878