Template-based peptide modeling for celiac risk assessment of newly expressed proteins in GM crops.

Newly expressed proteins in genetically modified (GM) crops are subject to celiac disease risk assessment according to EFSA guidelines. Amino acid identity matches between short peptides (9aa) and known celiac restricted epitopes are required to be further evaluated through peptide modeling; however, validated methods and criteria are not yet available. In this investigation, several structures of HLA-DQ2.5/peptide/TCR (T-cell receptor) complexes were analyzed and two template-based peptide molding software packages were evaluated using various peptides including ones not associated with celiac disease. Structural characterization indicates that residues at P(position)1, P2, P5, P8, and P9 in the 9aa restricted epitopes also contribute to the binding of celiac peptides to the HLA-DQ2.5 antigen in addition to the presence of the motif Q/EX1PX2 starting at P4 or P6. The recognition of the HLA-DQ2.5/peptide complex by TCR is through specific interactions between the residues in the restricted epitopes and some loop structures in the TCR. The template-based software package GalaxyPepDock seems to be suitable for the application of peptide modeling when an estimated accuracy value of >0.95 combined with >160 interaction similarity score are used as a threshold for biologically meaningful in silico binding. Nevertheless, caution should be exercised when applying peptide modeling to celiac disease risk assessment until methods are rigorously validated and further evaluated to demonstrate its value in the risk assessment of newly expressed proteins in GM crops.

Information Theory in Computational Biology: Where We Stand Today.

"A Mathematical Theory of Communication" was published in 1948 by Claude Shannon to address the problems in the field of data compression and communication over (noisy) communication channels. Since then, the concepts and ideas developed in Shannon's work have formed the basis of information theory, a cornerstone of statistical learning and inference, and has been playing a key role in disciplines such as physics and thermodynamics, probability and statistics, computational sciences and biological sciences. In this article we review the basic information theory based concepts and describe their key applications in multiple major areas of research in computational biology-gene expression and transcriptomics, alignment-free sequence comparison, sequencing and error correction, genome-wide disease-gene association mapping, metabolic networks and metabolomics, and protein sequence, structure and interaction analysis.

DBSI server: DNA binding site identifier.

UNLABELLED: : Protein-nucleic acid interactions are among the most important intermolecular interactions in the regulation of cellular events. Identifying residues involved in these interactions from protein structure alone is an important challenge. Here we introduce the webserver interface to DNA Binding Site Identifier (DBSI), a powerful structure-based SVM model for the prediction and visualization of DNA binding sites on protein structures. DBSI has been shown to be a top-performing model to predict DNA binding sites on the surface of a protein or peptide and shows promise in predicting RNA binding sites. AVAILABILITY AND IMPLEMENTATION: Server is available at http://dbsi.mitchell-lab.org CONTACT: jcmitchell@wisc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mitochondrial COQ9 is a lipid-binding protein that associates with COQ7 to enable coenzyme Q biosynthesis.

Coenzyme Q (CoQ) is an isoprenylated quinone that is essential for cellular respiration and is synthesized in mitochondria by the combined action of at least nine proteins (COQ1-9). Although most COQ proteins are known to catalyze modifications to CoQ precursors, the biochemical role of COQ9 remains unclear. Here, we report that a disease-related COQ9 mutation leads to extensive disruption of the CoQ protein biosynthetic complex in a mouse model, and that COQ9 specifically interacts with COQ7 through a series of conserved residues. Toward understanding how COQ9 can perform these functions, we solved the crystal structure of Homo sapiens COQ9 at 2.4 Å. Unexpectedly, our structure reveals that COQ9 has structural homology to the TFR family of bacterial transcriptional regulators, but that it adopts an atypical TFR dimer orientation and is not predicted to bind DNA. Our structure also reveals a lipid-binding site, and mass spectrometry-based analyses of purified COQ9 demonstrate that it associates with multiple lipid species, including CoQ itself. The conserved COQ9 residues necessary for its interaction with COQ7 comprise a surface patch around the lipid-binding site, suggesting that COQ9 might serve to present its bound lipid to COQ7. Collectively, our data define COQ9 as the first, to our knowledge, mammalian TFR structural homolog and suggest that its lipid-binding capacity and association with COQ7 are key features for enabling CoQ biosynthesis.