title: Connectivity independent protein-structure alignment: a hierarchical approach.
abstract: BACKGROUND
  Protein-structure alignment is a fundamental tool to study protein function, evolution and model building. In the last decade several methods for structure alignment were introduced, but most of them ignore that structurally similar proteins can share the same spatial arrangement of secondary structure elements (SSE) but differ in the underlying polypeptide chain connectivity (non-sequential SSE connectivity).
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  As demonstrated for several applications, GANGSTA finds meaningful protein-structure alignments independent of the SSE connectivity. GANGSTA is able to detect structural similarity of protein folds that are assigned to different superfamilies but nevertheless possess similar structures and perform related functions, even if these proteins differ in SSE connectivity.
authors.affiliation: Macromolecular Modeling Group, Institute of Chemistry and Biochemistry, FU Berlin, Takustrasse 6, 14195 Berlin, Germany. bjko@chemie.fu-berlin.de <bjko@chemie.fu-berlin.de>
authors.forename: Bjoern
authors.initials: B
authors.lastname: Kolbeck
authors.forename: Patrick
authors.initials: P
authors.lastname: May
authors.forename: Tobias
authors.initials: T
authors.lastname: Schmidt-Goenner
authors.forename: Thomas
authors.initials: T
authors.lastname: Steinke
authors.forename: Ernst-Walter
authors.initials: EW
authors.lastname: Knapp
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D019295:Computational Biology; D003196:Computer Graphics; D030541:Databases, Genetic; D008958:Models, Molecular; D011487:Protein Conformation; D017510:Protein Folding; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000235:genetics; D015203:Reproducibility of Results; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software
chemical_list: D011506:Proteins