Identification of catalytic residues from protein structure using support vector machine with sequence and structural features

Pugalenthi Ganesan, K. Krishna Kumar, P. N. Suganthan*, Rajeev Gangal

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    34 Scopus citations

    Abstract

    Identification of catalytic residues can provide valuable insights into protein function. With the increasing number of protein 3D structures having been solved by X-ray crystallography and NMR techniques, it is highly desirable to develop an efficient method to identify their catalytic sites. In this paper, we present an SVM method for the identification of catalytic residues using sequence and structural features. The algorithm was applied to the 2096 catalytic residues derived from Catalytic Site Atlas database. We obtained overall prediction accuracy of 88.6% from 10-fold cross validation and 95.76% from resubstitution test. Testing on the 254 catalytic residues shows our method can correctly predict all 254 residues. This result suggests the usefulness of our approach for facilitating the identification of catalytic residues from protein structures.

    Original languageEnglish (US)
    Pages (from-to)630-634
    Number of pages5
    JournalBiochemical and Biophysical Research Communications
    Volume367
    Issue number3
    DOIs
    StatePublished - Mar 14 2008

    Keywords

    • Active site
    • Functional residues
    • Protein function prediction
    • Sequence-structural features
    • Spatial neighbors

    ASJC Scopus subject areas

    • Biophysics
    • Biochemistry
    • Molecular Biology
    • Cell Biology

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