Cluster Algorithm for Protein Secondary Structure Prediction

Abstract

Protein structure determination and prediction has been a focal research subject in the area of drug discovery due to the importance of protein structure in understanding the biological and chemical activities of organisms. The experimental methods used to determine the structures of proteins demand sophisticated equipment and time. A host of computational methods are developed to predict the location of secondary structure elements in proteins for complementing or creating insights into experimental results. The present paper focuses on secondary structure prediction of proteins. The chou-fasman method is implemented to predict the various parameters related to the secondary structure. These parameters include the alpha helix, beta sheets and hairpin turn. The computation is based on cluster algorithm.