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

by: RW Montalvão, RE Smith, SC Lovell, TL Blundell

Bioinformatics, Vol. 21, No. 19. (1 October 2005), pp. 3719-3725.

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Abstract

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.

@article{citeulike:532004, abstract = {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.}, address = {Department of Biochemistry, University of Cambridge Tennis Court Road, Cambridge CB2 1GA, UK. rinaldo@cryst.bioc.cam.ac.uk}, author = {Montalv\~{a}o, R. W. and Smith, R. E. and Lovell, S. C. and Blundell, T. L. }, citeulike-article-id = {532004}, issn = {1367-4803}, journal = {Bioinformatics}, keywords = {comparative\_modeling, protein\_structure, structure\_prediction}, month = {October}, number = {19}, pages = {3719--3725}, posted-at = {2006-05-04 17:00:59}, priority = {2}, title = {CHORAL: a differential geometry approach to the prediction of the cores of protein structures.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/16046494}, volume = {21}, year = {2005} }

RIS record

TY - JOUR ID - citeulike:532004 L3 - citeulike-article-id:532004 N2 - 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. IS - 19 JF - Bioinformatics SN - 1367-4803 AD - Department of Biochemistry, University of Cambridge Tennis Court Road, Cambridge CB2 1GA, UK. rinaldo@cryst.bioc.cam.ac.uk EP - 3725 TI - CHORAL: a differential geometry approach to the prediction of the cores of protein structures. VL - 21 SP - 3719 KW - comparative_modeling KW - protein_structure KW - structure_prediction AU - Montalvão, RW AU - Smith, RE AU - Lovell, SC AU - Blundell, TL PY - 2005/10/01/ UR - http://view.ncbi.nlm.nih.gov/pubmed/16046494 ER -

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