Prediction of protein secondary structure based on residue pair types and conformational states using dynamic programming algorithm

Abstract

We have used a statistical approach for protein secondary structure prediction based on information theory and simultaneously taking into consideration pairwise residue types and conformational states. Since the prediction of residue secondary structure by one residue window sliding make ambiguity in state prediction, we used a dynamic programming algorithm to find the path with maximum score. A score system for residue pairs in particular conformations is derived for adjacent neighbors up to ten residue apart in sequence. The three state overall per-residue accuracy, Q 3, of this method in a jackknife test with dataset created from PDBSELECT is more than 70%.