Identification of catalytic residues from protein structure using support vector machine with sequence and structural features.
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.
Pugalenthi
Ganesan
G
School of Electrical and Electronic Engineering, Nanyang Technological University, Block S2, 50 Nanyang Avenue, Singapore 639798, Singapore.
Kumar
K Krishna
KK
Suganthan
P N
PN
Gangal
Rajeev
R
D000465:Algorithms; D020134:Catalytic Domain; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D030562:Databases, Protein; D011237:Predictive Value of Tests; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D015203:Reproducibility of Results
D011506:Proteins