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 language||English (US)|
|Number of pages||5|
|Journal||Biochemical and biophysical research communications|
|State||Published - Mar 14 2008|
Bibliographical noteFunding Information:
G.P. and P.N.S. acknowledge the financial support offered by the A∗Star (Agency for Science, Technology and Research). Authors thank Professor Dmitrij Frishman for his comments on this work.
- Active site
- Functional residues
- Protein function prediction
- Sequence-structural features
- Spatial neighbors
ASJC Scopus subject areas
- Molecular Biology
- Cell Biology