Quasi-consensus-based comparison of profile hidden Markov models for protein sequences

Abstract

A simple approach for the sensitive detection of distant relationships among protein families and for sequence–structure alignment via comparison of hidden Markov models based on their quasi-consensus sequences is presented. Using a previously published benchmark dataset, the approach is demonstrated to give better homology detection and yield alignments with improved accuracy in comparison to an existing state-of-the-art dynamic programming profile–profile comparison method. This method also runs significantly faster and is therefore suitable for a server covering the rapidly increasing structure database. A server based on this method is available at http://liao.cis.udel.edu/website/servers/modmod Contact:roland.dunbrack@fccc.edu; lliao@mail.eecis.udel.edu