title: Detection of unrelated proteins in sequences multiple alignments by using predicted secondary structures.
abstract: BACKGROUND
  Multiple sequence alignments are essential tools for establishing the homology relations between proteins. Essential amino acids for the function and/or the structure are generally conserved, thus providing key arguments to help in protein characterization. However for distant proteins, it is more difficult to establish, in a reliable way, the homology relations that may exist between them. In this article, we show that secondary structure prediction is a valuable way to validate protein families at low identity rate.
  
  
  RESULTS
  We show that the analysis of the secondary structures compatibility is a reliable way to discard non-related proteins in low identity multiple alignment.
  
  
  BACKGROUND
  This validation is possible through our NPS@ server (http://npsa-pbil.ibcp.fr)
authors.affiliation: Pôle de BioInformatique Lyonnais, Institut de Biologie et de Chimie des Protéines, Centre National de la Recherche Scientifique, UMR 5086, 69367 Lyon CEDEX 07, France.
authors.forename: Mounir
authors.initials: M
authors.lastname: Errami
authors.forename: Christophe
authors.initials: C
authors.lastname: Geourjon
authors.forename: Gilbert
authors.initials: G
authors.lastname: Deléage
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001483:Base Sequence; D030562:Databases, Protein; D011487:Protein Conformation; D017433:Protein Structure, Secondary; D011506:Proteins / Q000032:analysis* / Q000737:chemistry* / Q000145:classification; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D015842:Serine Proteinase Inhibitors / Q000032:analysis / Q000737:chemistry
chemical_list: D011506:Proteins; D015842:Serine Proteinase Inhibitors