Abstract
Protein-structure alignment is a fundamental tool to study protein function, evolution and model building. We perform protein-structure alignment using a two-level hierarchical approach implemented in the program GANGSTA. On the first level, pair contacts and relative orientations between SSEs (i.e. alpha-helices and beta-strands) are maximized with a genetic algorithm (GA). On the second level residue pair contacts from the best SSE alignments are optimized. We have tested the method on visually optimized structure alignments of protein pairs (pairwise mode) and for database scans. For a given protein structure, our method is able to detect significant structural similarity of functionally important folds with non- sequential SSE connectivity. The performance for structure alignments with strictly sequential SSE connectivity is comparable to that of other structure alignment methods.

Citation
"Connectivity independent protein-structure alignment: a hierarchical approach Bjoern Kolbeck, Patrick May, Tobias Schmidt-Goenner, Thomas Steinke and Ernst-Walter Knapp, BMC Bioinformatics 2006, 7:510"