Prediction of Protein Catalytic Residues by Local Structural Rigidity

Abstract

Due to the large number of protein structures whose functions are unknown, it becomes increasing important to study the structural characteristics of catalytic residues. Here, we use a novel method to calculate the local structural rigidity (LSR) of protein. Based on a dataset of 760 proteins, the results show that catalytic residues have distinct structural properties. They are shown to be extremely rigid based on the calculation of LSR. Finally, we present a machine-learning based method to predict catalytic residues from protein structure using LSR as primary input feature. The prediction sensitivity and specificity are 0.86 and 0.86, respectively, and the Matthew's correlation coefficient is 0.72.