CHORAL: a differential geometry approach to the prediction of the cores of protein structures.
BACKGROUND
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.
Montalvão
Rinaldo W
RW
Department of Biochemistry, University of Cambridge Tennis Court Road, Cambridge CB2 1GA, UK. rinaldo@cryst.bioc.cam.ac.uk
Smith
Richard E
RE
Lovell
Simon C
SC
Blundell
Tom L
TL
D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods; D011487:Protein Conformation; D011506:Proteins / Q000032:analysis / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D012984:Software
D011506:Proteins