Exploring protein structural dissimilarity to facilitate structure classification.

ABSTRACT:

Background

Classification of newly resolved protein structures is important in understanding their architectural, evolutionary and functional relatedness to known protein structures. Among various efforts to improve the database of Structural Classification of Proteins (SCOP), automation has received particular attention. Herein, we predict the deepest SCOP structural level that an unclassified protein shares with classified proteins with an equal number of secondary structure elements (SSEs).

Results

We compute a coefficient of dissimilarity (Omega) between proteins, based on structural and sequence-based descriptors characterising the respective constituent SSEs. For a set of 1,661 pairs of proteins with sequence identity up to 35%, the performance of Omega in predicting s

SUBMITTER: Jain P 

PROVIDER: S-EPMC2754988 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature