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RTN1-C protein is a membrane protein localized in the ER and expressed in the nervous system. Its biological role is still unclear, although interactions of the N-terminal region of RTN1-C with proteins involved in vesicle trafficking have been observed, but the role of the C-terminal region of this family protein remains to be investigated. By a homology analysis of the amino acid sequence, we identified in the C-terminal region of RTN1-C a unique consensus sequence characteristic of H4 histone protein. Thus, a 23-mer peptide (RTN1-C(CT)) corresponding to residues 186-208 of RTN1-C was synthesized, and its conformation and its interaction with nucleic acids were investigated. Here we demonstrate the strong ability of RTN1-C(CT) peptide to bind and condense the nucleic acids using electrophoretic and spectroscopic techniques. To determine if the binding of RTN1-C to nucleic acids could be regulated in vivo by an acetylation-deacetylation mechanism, as for the histone proteins, we studied the interaction of RTN1-C with one zinc-dependent histone deacetylase (HDAC) enzyme, HDAC8, with fluorescence and kinetic techniques using an acetylated form of RTN1-C(CT). The results reported here allow us to propose that the nucleic acid binding property of RTN1-C may have an important role in the biological function of this protein, the function of which could be regulated by an acetylation-deacetylation mechanism.

Background Multiple sequence alignments are a fundamental tool for the comparative analysis of proteins and nucleic acids. However, large data sets are no longer manageable for visualization and investigation using the traditional stacked sequence alignment representation. Results We introduce ProfileGrids that represent a multiple sequence alignment as a matrix color-coded according to the residue frequency occurring at each column position. JProfileGrid is a Java application for computing and analyzing ProfileGrids. A dynamic interaction with the alignment information is achieved by changing the ProfileGrid color scheme, by extracting sequence subsets at selected residues of interest, and by relating alignment information to residue physical properties. Conserved family motifs can be identified by the overlay of similarity plot calculations on a ProfileGrid. Figures suitable for publication can be generated from the saved spreadsheet output of the colored matrices as well as by the export of conservation information for use in the PyMOL molecular visualization program. We demonstrate the utility of ProfileGrids on 300 bacterial homologs of the RecA family – a universally conserved protein involved in DNA recombination and repair. Careful attention was paid to curating the collected RecA sequences since ProfileGrids allow the easy identification of rare residues in an alignment. We relate the RecA alignment sequence conservation to the following three topics: the recently identified DNA binding residues, the unexplored MAW motif, and a unique Bacillus subtilis RecA homolog sequence feature. Conclusion ProfileGrids allow large protein families to be visualized more effectively than the traditional stacked sequence alignment form. This new graphical representation facilitates the determination of the sequence conservation at residue positions of interest, enables the examination of structural patterns by using residue physical properties, and permits the display of rare sequence features within the context of an entire alignment. JProfileGrid is free for non-commercial use and is available from http://www.profilegrid.org. Furthermore, we present a curated RecA protein collection that is more diverse than previous data sets; and, therefore, this RecA ProfileGrid is a rich source of information for nanoanatomy analysis.