A geometric clustering algorithm has been developed to dissect protein fragments based on their relevance to function

Brener, Nathan E

Iyengar, Sitharama S

Manikandan, Karuppasamy

Pal, Debnath

Ramakumar, Suryanarayanarao

Seetharaman, Guna

English

PubMed

Karuppasamy Manikandan

Debnath Pal

Suryanarayanarao Ramakumar

Nathan E Brener

Sitharama S Iyengar

Guna Seetharaman

Springer - Publisher Connector

Functionally important segments in proteins dissected using Gene Ontology and geometric clustering of peptide fragments

We have developed a geometric clustering algorithm using backbone \varphi,\psi 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

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Functionally important segments in proteins dissected using Gene Ontology and geometric clustering of peptide fragments

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Open Access Repository of IISc Research Publications

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Springer - Publisher Connector