Method
Functionally important segments in proteins dissected using Gene Ontology and geometric clustering of peptide fragments
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* Corresponding authors: Debnath Pal dpal@serc.iisc.ernet.in - Suryanarayanarao Ramakumar ramak@physics.iisc.ernet.in
1 Bioinformatics Centre, Indian Institute of Science, Bangalore 560012, India
2 Department of Physics, Indian Institute of Science, Bangalore 560012, India
3 Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560012, India
4 Department of Computer Science, Louisiana State University, Baton Rouge, LA 70803, USA
5 Main correspondence
Genome Biology 2008, 9:R52 doi:10.1186/gb-2008-9-3-r52
Published: 10 March 2008Abstract
We have developed a geometric clustering algorithm using backbone φ,ψ angles to group conformationally similar peptide fragments of any length. By labeling each fragment in the cluster with the level-specific Gene Ontology 'molecular function' term of its protein, we are able to compute statistics for molecular function-propensity and p-value of individual fragments in the cluster. Clustering-cum-statistical analysis for peptide fragments 8 residues in length and with only trans peptide bonds shows that molecular function propensities ≥20 and p-values ≤0.05 can dissect fragments within a protein linked to the molecular function.