CHORAL: a differential geometry approach to the prediction of the cores of protein structures

MOTIVATION Although the cores of homologous proteins are relatively well conserved, amino acid substitutions lead to significant differences in the structures of divergent superfamilies. Thus, the classification of amino acid sequence patterns and the selection of appropriate fragments of the protein cores of homologues of known structure are important for accurate comparative modelling. RESULTS CHORAL utilizes a knowledge-based method comprising an amalgam of differential geometry and pattern recognition algorithms to identify conserved structural patterns in homologous protein families. Propensity tables are used to classify and to select patterns that most likely represent the structure of the core for a target protein. In our benchmark, CHORAL demonstrates a performance equivalent to that of MODELLER.

[1]  T. Blundell,et al.  Comparative protein modelling by satisfaction of spatial restraints. , 1993, Journal of molecular biology.

[2]  D. Schomburg,et al.  Prediction of protein three-dimensional structures in insertion and deletion regions: a procedure for searching data bases of representative protein fragments using geometric scoring criteria. , 1995, Journal of molecular biology.

[3]  Michael J. Sutcliffe,et al.  Knowledge-based protein modelling , 1989 .

[4]  M C Peitsch,et al.  ProMod and Swiss-Model: Internet-based tools for automated comparative protein modelling. , 1996, Biochemical Society transactions.

[5]  T. Blundell,et al.  Knowledge based modelling of homologous proteins, Part I: Three-dimensional frameworks derived from the simultaneous superposition of multiple structures. , 1987, Protein engineering.

[6]  John P. Overington,et al.  Knowledge‐based protein modelling and design , 1988 .

[7]  C. Deane,et al.  CODA: A combined algorithm for predicting the structurally variable regions of protein models , 2001, Protein science : a publication of the Protein Society.

[8]  John P. Overington,et al.  Fragment ranking in modelling of protein structure. Conformationally constrained environmental amino acid substitution tables. , 1993, Journal of molecular biology.

[9]  R. Huber,et al.  Accurate Bond and Angle Parameters for X-ray Protein Structure Refinement , 1991 .

[10]  John P. Overington,et al.  HOMSTRAD: A database of protein structure alignments for homologous families , 1998, Protein science : a publication of the Protein Society.

[11]  Sergios Theodoridis,et al.  Pattern Recognition , 1998, IEEE Trans. Neural Networks.

[12]  T. Blundell,et al.  Definition of general topological equivalence in protein structures. A procedure involving comparison of properties and relationships through simulated annealing and dynamic programming. , 1990, Journal of molecular biology.

[13]  Manuel C. Peitsch,et al.  SWISS-MODEL: an automated protein homology-modeling server , 2003, Nucleic Acids Res..

[14]  C. Deane,et al.  A novel exhaustive search algorithm for predicting the conformation of polypeptide segments in proteins , 2000, Proteins.

[15]  T. Blundell,et al.  Knowledge-based protein modeling. , 1994, Critical reviews in biochemistry and molecular biology.

[16]  Charlotte M. Deane,et al.  SCORE: predicting the core of protein models , 2001, Bioinform..

[17]  T L Blundell,et al.  An evaluation of the performance of an automated procedure for comparative modelling of protein tertiary structure. , 1993, Protein engineering.

[18]  J. Greer,et al.  Model for haptoglobin heavy chain based upon structural homology. , 1980, Proceedings of the National Academy of Sciences of the United States of America.

[19]  T L Blundell,et al.  Knowledge based modelling of homologous proteins, Part II: Rules for the conformations of substituted sidechains. , 1987, Protein engineering.

[20]  M. Levitt Accurate modeling of protein conformation by automatic segment matching. , 1992, Journal of molecular biology.