PROFALIGN algorithm identifies the regions containing folding determinants by scoring pairs of hydrophobic profiles of remotely related proteins.

Profile comparison methods have been shown to be very powerful in creating accurate alignments of protein sequences, especially in the case of remotely related proteins (RRP). These methods take advantage of the observation that hydrophobic profiles are more conserved than the corresponding amino acid sequences. Here, we present the PROFALIGN algorithm, which allows one to perform a detailed comparative analysis, at both local and global levels of two protein sequence profiles. The user can either choose among four different hydrophobic scales (Miyazawa-Jernigan, Eisenberg, Engelman-Steiz, and Kyte-Doolittle) or can add a personal scale. The interface is designed for a wide range of users, including those who are not involved in protein research. It allows one to vary the alignment parameters (such as gap penalties, embedding, and profile smoothness). Secondary structure propensity is added as an optional alignment filter. Similar segments of two proteins are singled out on the basis of score. We have tested the algorithm with different Src homology 3 (SH3) domain fragments sharing low sequence homology but very similar three-dimensional (3D) structures. By using the Miyazawa-Jernigan hydrophobic scale, PROFALIGN was able to detect the strong correlation between the regions that are known to be crucial for SH3 transition state topology. PROFALIGN seems able to identify most of the mutual alignment of structures on the basis of their hydrophobic profiles, delimiting the regions containing the key determinants of folding. Therefore, the present methodology may be useful for the detection of the most structurally relevant positions inside remote related proteins.

Isolation of flagellated bacteria implicated in Crohn's disease.

BACKGROUND: Serologic expression cloning has identified flagellins of the intestinal microbiota as immunodominant antigens in experimental colitis in mice and in individuals with Crohn's disease (CD). The present study was done to identify the microbial source of such flagellins. METHODS: Using a variety of isolation and culture approaches, a number of previously unknown flagellated bacteria were isolated. Based on 16S ribosomal DNA sequences, these bacteria fall into the family Lachnospiraceae of the phylum Firmicutes. RESULTS: Serum IgG from patients with CD and from mice with colitis reacted to the flagellins of these bacteria, and only their flagellins, whereas serum IgG from controls did not. The sequence of these flagellins demonstrate conserved amino- and carboxy-terminal domains that cluster phylogenetically and have a predicted 3D structure similar to Salmonella fliC, including an intact TLR5 binding site. The flagellin of 1 of these bacteria was likely O-glycosylated. CONCLUSIONS: The conserved immune response in both mouse and human to these previously unknown flagellins of the microbiota indicate that they play an important role in host-microbe interactions in the intestine.

Peptides derived from the heptad repeat region near the C-terminal of Sendai virus F protein bind the hemagglutinin-neuraminidase ectodomain.

Previously, we showed that Sendai virus fusion protein (F) acts as an inhibitor of neuraminidase activity of hemagglutinin-neuraminidase (HN) protein. Here we report that synthetic peptides derived from the heptad repeat region proximal to the transmembrane domain (HR2) of Sendai virus F inhibit fusion and enhance the enzymatic activity of the HN. This occurs on the virus-bound HN and on its soluble globular head. The enhancing effect on virus-bound HN is reversible and depends on the presence of F. The data indicate that, by binding to the HN ectodomain, the HR2 peptides abolish the F inhibition of HN and disrupt the communication between the F and HN essential to promote virus-cell fusion.

Human ß2-glycoprotein I attenuates mouse intestinal ischemia/reperfusion induced injury and inflammation.

Intestinal ischemia-reperfusion (IR)-induced injury results from a complex cascade of inflammatory components. In the mouse model of intestinal IR, the serum protein, ß2-glycoprotein I (ß2-GPI) binds to the cell surface early in the cascade. The bound ß2-GPI undergoes a conformational change which exposes a neoantigen recognized by naturally occurring antibodies and initiates the complement cascade. We hypothesized that providing additional antigen with exogenous ß2-GPI would alter IR-induced tissue injury. Administration of human but not mouse ß2-GPI attenuated IR-induced tissue damage and prostaglandin E(2) production indicating a physiological difference between ß2-GPI isolated from the two species. To investigate whether structural features were responsible for this physiological difference, we compared the chemical, physical and biochemical properties of the two proteins. Despite possessing 76% amino acid identity and 86% sequence homology, we found that mouse ß2-GPI differs from the human protein in size, carbohydrate chain location, heterogeneity and secondary structural content. These data suggest that the structural differences result in mouse Ab recognition of soluble human but not mouse ß2-GPI and attenuated IR-induced injury. We conclude that caution should be exercised in interpreting results obtained by using human ß2-GPI in a mouse model.

Recurrence quantification analysis reveals interaction partners in paramyxoviridae envelope glycoproteins.

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.