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 prote...

Full description

Saved in:
Bibliographic Details
Published inBioinformatics Vol. 21; no. 19; pp. 3719 - 3725
Main Authors Montalvão, Rinaldo W., Smith, Richard E., Lovell, Simon C., Blundell, Tom L.
Format Journal Article
LanguageEnglish
Published Oxford Oxford University Press 01.10.2005
Oxford Publishing Limited (England)
Subjects
Algorithms
Amino Acid Sequence
Biological and medical sciences
Computer Simulation
Fundamental and applied biological sciences. Psychology
General aspects
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Models, Chemical
Models, Molecular
Molecular Sequence Data
Pattern Recognition, Automated - methods
Protein Conformation
Proteins - analysis
Proteins - chemistry
Sequence Alignment - methods
Sequence Analysis, Protein - methods
Sequence Homology, Amino Acid
Software
Differential geometry
Prediction
Identification
Review
Pattern recognition
Knowledge
Protein
Classification
Models
Web site
Structure
Bioinformatics
Comparative study
Online AccessGet full text

Cover

More Information
Summary: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. Availability: The algorithm is available via internet on http://www-cryst.bioc.cam.ac.uk/servers.html Contact: rinaldo@cryst.bioc.cam.ac.uk
Bibliography:istex:E361EDFA9554B7DDC92555EE800BC8F71D008756
ark:/67375/HXZ-6QNZ967S-2
To whom correspondence should be addressed.
local:bti595
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ObjectType-Article-1
ObjectType-Feature-2
ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/bti595