Evidence for conservation and selection of upstream open reading frames suggests probable encoding of bioactive peptides

Background: Approximately 40% of mammalian mRNA sequences contain AUG trinucleotides upstream of the main coding sequence, with a quarter of these AUGs demarcating open reading frames of 20 or more codons. In order to investigate whether these open reading frames may encode functional peptides, we have carried out a comparative genomic analysis of human and mouse mRNA 'untranslated regions' using sequences from the RefSeq mRNA sequence database. Results: We have identified over 200 upstream open reading frames which are strongly conserved between the human and mouse genomes. Consensus sequences associated with efficient initiation of translation are overrepresented at the AUG trinucleotides of these upstream open reading frames, while comparative analysis of their DNA and putative peptide sequences shows evidence of purifying selection. Conclusion: The occurrence of a large number of conserved upstream open reading frames, in association with features consistent with protein translation, strongly suggests evolutionary maintenance of the coding sequence and indicates probable functional expression of the peptides encoded within these upstream open reading frames.

Immunogenicity of liposomes containing lipid core peptides and the adjuvant Quil A

Purpose. The purpose of this study was to investigate the immunogenicity of liposomes containing mannosylated lipid core peptide (manLCP) constructs, both in vitro and in vivo, with or without the addition of the immune stimulating adjuvant Quil A. Methods. Mouse bone marrow dendritic cells (BMDC) were cultured with liposome formulations for 48 h, and the resulting level of BMDC activation was determined by flow cytometry. BMDC pulsed with liposome formulations were incubated with 5,6-carboxyfluoroscein diacetate succinimidyl ester-labeled T cells for 72 h and the resulting T cell proliferation was determined by flow cytometry. To investigate the immunogenicity of formulations in vivo, groups of C57Bl/6J mice were immunized by subcutaneous injection, and the resulting antigen-specific cytotoxic and protective immune responses toward tumor challenge evaluated. Results. Despite being unable to demonstrate the activation of BMDC, BMDC pulsed with liposomes containing manLCP constructs were able to stimulate the proliferation of naive T cells in vitro. However, in vivo only liposomes containing both manLCP and Quil A were able to stimulate a strong antigen-specific cytotoxic immune response. Liposomes containing manLCP and Quil A within the same particle were able to protect against the growth of tumor cells to a similar level as if the antigen was administered in alum with CD4 help. Conclusion. ManLCPs administered in liposomes are able to stimulate strong cytotoxic and protective immune responses if Quil A is also incorporated as an adjuvant.

Prediction of HLA-DQ3.2 beta ligands: evidence of multiple registers in class II binding peptides

Motivation: While processing of MHC class II antigens for presentation to helper T-cells is essential for normal immune response, it is also implicated in the pathogenesis of autoimmune disorders and hypersensitivity reactions. Sequence-based computational techniques for predicting HLA-DQ binding peptides have encountered limited success, with few prediction techniques developed using three-dimensional models. Methods: We describe a structure-based prediction model for modeling peptide-DQ3.2 beta complexes. We have developed a rapid and accurate protocol for docking candidate peptides into the DQ3.2 beta receptor and a scoring function to discriminate binders from the background. The scoring function was rigorously trained, tested and validated using experimentally verified DQ3.2 beta binding and non-binding peptides obtained from biochemical and functional studies. Results: Our model predicts DQ3.2 beta binding peptides with high accuracy [area under the receiver operating characteristic (ROC) curve A(ROC) > 0.90], compared with experimental data. We investigated the binding patterns of DQ3.2 beta peptides and illustrate that several registers exist within a candidate binding peptide. Further analysis reveals that peptides with multiple registers occur predominantly for high-affinity binders.

Protease-activated receptor-2 peptides activate neurokinin-1 receptors in the mouse isolated trachea

Protective roles for protease-activated receptor-2 (PAR2) in the airways including activation of epithelial chloride (Cl-) secretion are based on the use of presumably PAR(2)-selective peptide agonists. To determine whether PAR(2) peptide-activated Cl- secretion from mouse tracheal epithelium is dependent on PAR(2), changes in ion conductance across the epithelium [short-circuit current (I-SC)] to PAR(2) peptides were measured in Ussing chambers under voltage clamp. In addition, epithelium and endothelium-dependent relaxations to these peptides were measured in two established PAR(2) bioassays, isolated ring segments of mouse trachea and rat thoracic aorta, respectively. Apical application of the PAR(2) peptide SLIGRL caused increases in I-SC, which were inhibited by three structurally different neurokinin receptor-1 (NK1R) antagonists and inhibitors of Cl- channels but not by capsaicin, the calcitonin gene-related peptide (CGRP) receptor antagonist CGRP(8-37), or the nonselective cyclooxygenase inhibitor indomethacin. Only high concentrations of trypsin caused an increase in I-SC but did not affect the responses to SLIGRL. Relaxations to SLIGRL in the trachea and aorta were unaffected by the NK1R antagonist nolpitantium (SR 140333) but were abolished by trypsin desensitization. The rank order of potency for a range of peptides in the trachea I-SC assay was 2-furoyl-LIGRL > SLCGRL > SLIGRL > SLIGRT > LSIGRL compared with 2-furoyl-LIGRL > SLIGRL > SLIGRT > SLCGRL (LSIGRL inactive) in the aorta relaxation assay. In the mouse trachea, PAR(2) peptides activate both epithelial NK1R coupled to Cl- secretion and PAR(2) coupled to prostaglandin E-2-mediated smooth muscle relaxation. Such a potential lack of specificity of these commonly used peptides needs to be considered when roles for PAR(2) in airway function in health and disease are determined.

Synthesis of 'difficult' peptides free of aspartimide and related products, using peptoid methodology

We developed an efficient, cost effective strategy for Fmoc-based solid phase synthesis of 'difficult' peptides and/or peptides containing Asp/Asn-Gly sequences, free of aspartimide and related products, using a peptoid methodology for the preparation of N-substituted glycines.

The cyclotides and related macrocyclic peptides as scaffolds in drug design

The applicability of linear peptides as drugs is potentially limited by their susceptibility to proteolytic cleavage and poor bioavailability. Cyclotides are macrocyclic cystine-knotted mini-proteins that have a broad range of bioactivities and are exceptionally stable, being resistant to chemical, thermal and enzymatic degradation. The general limitations of peptides as drugs can potentially be overcome by using the cyclotide framework as a scaffold onto which new activities may be engineered. The potential use of cyclotides and related peptide scaffolds for drug design is evaluated herein, with reference to increasing knowledge of the structures and sequence diversity of natural cyclotides and the emergence of new approaches in protein engineering.

Detecting and sorting targeting peptides wtih neural networks and support vector machines

This paper presents a composite multi-layer classifier system for predicting the subcellular localization of proteins based on their amino acid sequence. The work is an extension of our previous predictor PProwler v1.1 which is itself built upon the series of predictors SignalP and TargetP. In this study we outline experiments conducted to improve the classifier design. The major improvement came from using Support Vector machines as a "smart gate" sorting the outputs of several different targeting peptide detection networks. Our final model (PProwler v1.2) gives MCC values of 0.873 for non-plant and 0.849 for plant proteins. The model improves upon the accuracy of our previous subcellular localization predictor (PProwler v1.1) by 2% for plant data (which represents 7.5% improvement upon TargetP).