Detection of unrelated proteins in sequences multiple alignments by using predicted secondary structures.

M. Errami (1) , C. Geourjon (1) , G. Deleage (1)

1 IBCP - Institut de biologie et chimie des protéines [Lyon]

MOTIVATION: 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. AVAILABILITY: This validation is possible through our NPS@ server (http://npsa-pbil.ibcp.fr)MOTIVATION: 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. AVAILABILITY: This validation is possible through our NPS@ server (http://npsa-pbil.ibcp.fr)

Domaines: Biochimie, Biologie Moléculaire

M. Errami, C. Geourjon, G. Deleage. Detection of unrelated proteins in sequences multiple alignments by using predicted secondary structures.. Bioinformatics, 2003, 19, pp.506-512. ⟨hal-00313744⟩