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Recurrence quantification analysis reveals interaction partners in paramyxoviridae envelope glycoproteins
Author(s) -
Giuliani Alessandro,
Tomasi Maurizio
Publication year - 2001
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.10044
Subject(s) - glycoprotein , hemagglutinin (influenza) , sequence (biology) , transmembrane protein , computational biology , fusion protein , protein–protein interaction , viral envelope , lipid bilayer fusion , biology , chemistry , virus , biophysics , virology , microbiology and biotechnology , genetics , recombinant dna , gene , receptor
Abstract The paramyxovirus envelope fuses with the host cell membrane by cooperative interaction of two transmembrane glycoproteins: the hemagglutinin neuraminidase (HN) and the fusion (F) glycoprotein. The interaction appears to be finely regulated, as both proteins must derive from the same viral species to obtain a functional interaction. Because HN and F do not form stable complexes, this interaction is poorly characterized. This article demonstrates that a modification of a classical bioinformatic method based on the co‐evolution of interacting partners can detect the specificity of the HN and F interaction. The proposed approach relies on a relatively new nonlinear signal analysis technique, recurrence quantification analysis (RQA), applied to the hydrophobicity sequences of viral proteins. This technique is able to shed light on the interaction between HN and F proteins in the virus–cell fusion and, more generally, permits the quantitative comparison of nonhomologue protein systems. On the contrary, the same co‐evolution approach, based on the classical sequence alignment procedure, was unable to discriminate interacting partners from the general strict correlation existing between the evolution of viral proteins as a whole. The cooperation between HN and F in the fusion process is thus demonstrated by a bioinformatic, purely sequence‐dependent, perspective. Proteins 2002;46:171–176. © 2001 Wiley‐Liss, Inc.