AN EVOLUTIONARY CONSERVATION-BASED METHOD FOR REFINING AND RERANKING PROTEIN COMPLEX STRUCTURES BAHAR AKBAL-DELIBAS * ,‡ , IRINA HASHMI †,§ , AMARDA SHEHU †,¶ and NURIT HASPEL * ,|| * Computer Science Department University of Massachusetts Boston 100 Morrissey Boulevard Boston, MA 02125, USA † Department of Computer Science George Mason University, 4400 University Drive Fairfax, VA 22030, USA ‡ abakbal@cs.umb.edu § ihashmi@gmu.edu ¶ amarda@gmu.edu || nurit.haspel@umb.edu Received 13 February 2012 Accepted 24 March 2012 Published 4 June 2012 Detection of protein complexes and their structures is crucial for understanding their role in the basic biology of organisms. Computational docking methods can provide researchers with a good starting point for the analysis of protein complexes. However, these methods are often not accurate and their results need to be further re¯ned to improve interface packing. In this paper, we introduce a re¯nement method that incorporates evolutionary information into a novel scoring function by employing Evolutionary Trace (ET)-based scores. Our method also takes Van der Waals interactions into account to avoid atomic clashes in re¯ned structures. We tested our method on docked candidates of eight protein complexes and the results suggest that the proposed scoring function helps bias the search toward complexes with native interactions. We show a strong correlation between evo- lutionary-conserved residues and correct interface packing. Our re¯nement method is able to produce structures with better lRMSD (least RMSD) with respect to the known complexes and lower energies than initial docked structures. It also helps to ¯lter out false-positive complexes generated by docking methods, by detecting little or no conserved residues on false interfaces. We believe this method is a step toward better ranking and prediction of protein complexes. Keywords: Docking re¯nement; interface conservation; evolutionary trace. || Corresponding author. Journal of Bioinformatics and Computational Biology Vol. 10, No. 3 (2012) 1242002 (15 pages) # . c Imperial College Press DOI: 10.1142/S0219720012420024 1242002-1 J. Bioinform. Comput. Biol. 2012.10. Downloaded from www.worldscientific.com by GEORGE MASON UNIVERSITY on 07/04/13. For personal use only.