title: Consistency matrices: quantified structure alignments for sets of related proteins.
abstract: Comparing two remotely similar structures is a difficult problem: more often than not, resulting structure alignments will show ambiguities and a unique answer usually does not even exist. In addition, alignments in general have a limited information content because every aligned residue is considered equally important. To solve these issues to a certain extent, one can take the perspective of a whole group of similar structures and then evaluate common structural features. Here, we describe a consistency approach that, although not actually performing a multiple structure alignment, does produce the information that one would conceivably want from such an experiment: the key structural features of the group, e.g., a fold, which in this case are projected onto either a pair of proteins or a single protein. Both representations are useful for a number of applications, ranging from the detection of (partially) wrong structure alignments to protein structure classification and fold recognition. To demonstrate some of these applications, the procedure was applied to 195 SCOP folds containing a total of 1802 domains sharing very low sequence similarity.
authors.affiliation: Department of Ultrastructure, Vrije Universiteit Brussel, Sint-Genesius Rode, Belgium. ivwalle@vub.ac.be
authors.forename: Ivo
authors.initials: I
authors.lastname: Van Walle
authors.forename: Ignace
authors.initials: I
authors.lastname: Lasters
authors.forename: Lode
authors.initials: L
authors.lastname: Wyns
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D017510:Protein Folding; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000145:classification; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D011506:Proteins