Tertiary structure-based protein classification by virtual-bond-angles series

Abstract

Structure-based protein classification can be based on the similarities in primary, second or tertiary structures of proteins. A method using virtual-bond-angles series that transformed the protein space configuration into a sequence was used for the classification of three-dimensional structures of proteins. By transforming the main chains formed by Cα atoms of proteins into sequences, the series of virtual-bond-angles corresponding to the tertiary structure of the proteins were constructed. Then a distance-based hierarchical clustering method similar to Ward method was introduced to classify these virtual-bond-angles series of proteins. 200 files of protein structures were selected from Brookheaven protein data bank, and 11 clusters were classified.