Project : Development of knowledge based computational methods for protein structure prediction

	The gap between the known protein sequences and experimentally solved, three dimensional (3D) protein structures is very large, and continues to grow as genome sequencing projects are encompassing more and more organisms. As 3D structure of protein gives important information about its function, closing the gap by means of predicting the 3D structures is of great scientific and medical importance. In this context, the aim of our group is to develop new knowledge-based computational procedures for protein structure and function prediction and to learn some sequence-structure relationship. Currently, we are developing a machine learning approach for protein fold recognition using sequence and structural features of amino acid residues as discriminatory features. People involved
		Md Tabrez Anwar Shamim Senior Research Fellow
		Mohammad Anwaruddin Project Assistant

Publications

Research Articles

Shamim, M.T.A.; Anwaruddin, M. and Nagarajaram, H.A. Support Vector Machine based fold-wise classification of proteins using the structural properties of amino acid residues and amino acid residue pairs (Manuscript under preparation)

Posters Presented

Shamim, M.T.A. and Nagarajaram, H.A.: "Knowledge Based Approach For Protein Fold Recognition." presented at INCOB, 2006 New Delhi.

Anwaruddin, M.; Chalissery, J.; Sen, R. and Nagarajaram, H. A.: "Structural analysis of Rho mutants through molecular dynamics simulations." presented at INCOB, 2006 New Delhi.