A NEW APPROACH TO PROTEIN FOLD RECOGNITION

被引:970
|
作者
JONES, DT [1 ]
TAYLOR, WR [1 ]
THORNTON, JM [1 ]
机构
[1] NATL INST MED RES,MATH BIOL LAB,LONDON NW7 1AA,ENGLAND
关键词
D O I
10.1038/358086a0
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
THE prediction of protein tertiary structure from sequence using molecular energy calculations has not yet been successful; an alternative strategy of recognizing known motifs 1 or folds 2-4 in sequences looks more promising. We present here a new approach to fold recognition, whereby sequences are fitted directly onto the backbone coordinates of known protein structures. Our method for protein fold recognition involves automatic modelling of protein structures using a given sequence, and is based on the frameworks of known protein folds. The plausibility of each model, and hence the degree of compatibility between the sequence and the proposed structure, is evaluated by means of a set of empirical potentials derived from proteins of known structure. The novel aspect of our approach is that the matching of sequences to backbone coordinates is performed in full three-dimensional space, incorporating specific pair interactions explicitly.
引用
收藏
页码:86 / 89
页数:4
相关论文
共 50 条
  • [1] A new approach to protein fold recognition based on Delaunay tessellation of protein structure
    Zheng, W
    Cho, SJ
    Vaisman, II
    Tropsha, A
    [J]. PACIFIC SYMPOSIUM ON BIOCOMPUTING '97, 1996, : 486 - 497
  • [2] Cooperative approach for the protein fold recognition
    Ota, M
    Kawabata, T
    Kinjo, AR
    Nishikawa, K
    [J]. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 1999, : 126 - 132
  • [3] A new approach to protein fold recognition based on delaunay tessellation of protein structure.
    Tropsha, A
    Vaisman, II
    Cho, SJ
    Zheng, W
    [J]. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 1996, 212 : 71 - COMP
  • [4] Segmentation conditional random fields (SCRFs): A new approach for protein fold recognition
    Liu, Y
    Carbonell, J
    Weigele, P
    Gopalakrishnan, V
    [J]. RESEARCH IN COMPUTATIONAL MOLECULAR BIOLOGY, PROCEEDINGS, 2005, 3500 : 408 - 422
  • [5] A NEW CLASSIFIER FOR PROTEIN FOLD CLASS RECOGNITION
    Yanev, Nicola
    Traykov, Metodi
    Milanov, Peter
    Yurukov, Borislav
    [J]. COMPTES RENDUS DE L ACADEMIE BULGARE DES SCIENCES, 2018, 71 (07): : 885 - 892
  • [6] A hybrid discriminative/generative approach to protein fold recognition
    Chmielnicki, Wieslaw
    Stapor, Katarzyna
    [J]. NEUROCOMPUTING, 2012, 75 (01) : 194 - 198
  • [7] PROTEIN FOLD RECOGNITION
    SHORTLE, D
    [J]. NATURE STRUCTURAL BIOLOGY, 1995, 2 (02): : 91 - 93
  • [8] PROTEIN FOLD RECOGNITION
    JONES, D
    THORNTON, J
    [J]. JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN, 1993, 7 (04) : 439 - 456
  • [9] A machine learning information retrieval approach to protein fold recognition
    Cheng, Jianlin
    Baldi, Pierre
    [J]. BIOINFORMATICS, 2006, 22 (12) : 1456 - 1463
  • [10] A new taxonomy-based protein fold recognition approach based on autocross-covariance transformation
    Dong, Qiwen
    Zhou, Shuigeng
    Guan, Jihong
    [J]. BIOINFORMATICS, 2009, 25 (20) : 2655 - 2662