Detection of unrelated proteins in sequences multiple alignments by using predicted secondary structures.
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)
Errami
Mounir
M
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.
Geourjon
Christophe
C
Deléage
Gilbert
G
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
D011506:Proteins; D015842:Serine Proteinase Inhibitors