G-protein-coupled receptors (GPCRs) represent an important group of targets for pharmaceutical therapeutics. The completion of the human genome revealed a large number of putative GPCRs. However, the identification of their natural ligands, and especially peptides, suffers from low discovery rates, thus impeding development of therapeutics based on these potential drug targets. We describe the discovery of novel GPCR ligands encrypted in the human proteome. Hundreds of potential peptide ligands were predicted by machine learning algorithms. In vitro screening of selected 33 peptides on a set of 152 GPCRs, including a group of designated orphan receptors, was conducted by intracellular calcium measurements and cAMP assays. The screening revealed eight novel peptides as potential agonists that specifically activated six different receptors in a dose-dependent manner. Most of the peptides showed distinct stimulatory patterns targeted at designated and orphan GPCRs. Further analysis demonstrated a significant in vivo effect for one of the peptides in a mouse inflammation model.
Pulmonary fibrosis is a progressive and lethal lung disease characterized by accumulation of extracellular matrix and loss of pulmonary function. No cure exists for this pathologic condition, and current treatments often fail to slow its progression or relieve its symptoms. Relaxin was previously shown to induce a matrix-degrading phenotype in human lung fibroblasts in vitro and to inhibit pulmonary fibrosis in vivo. A novel peptide that targets the relaxin RXFP1/LGR7 receptor was recently identified using our computational platform designed to predict novel G protein-coupled receptor peptide agonists. In this study, we examined the antifibrotic properties of this novel peptide, designated CGEN25009, in human cell-based assays and in a murine model of bleomycin-induced pulmonary fibrosis. Similar to relaxin, CGEN25009 was found to have an inhibitory effect on transforming growth factor-1-induced collagen deposition in human dermal fibroblasts and to enhance MMP-2 expression. The peptide's biological activity was also similar to relaxin in generating cellular stimulation of cAMP, cGMP, and NO in the THP-1 human cell line. In vivo, 2-week administration of CGEN25009 in a preventive or therapeutic mode (i.e., concurrently with or 7 days after bleomycin treatment, respectively) caused a significant reduction in lung inflammation and injury and ameliorated adverse airway remodeling and peribronchial fibrosis. The results of this study indicate that CGEN25009 displays antifibrotic and anti-inflammatory properties and may offer a new therapeutic option for the treatment of pulmonary fibrosis.
Identification of proteins using matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) peptide mass fingerprinting (PMF) is a key technique in proteomics. The method is known to be sensitive as well as amenable to high-throughput operation, but the resulting identifications suffer from a relatively low level of confidence. One way of increasing the confidence is by improving measurement accuracy using one of several calibration methods. This paper presents a new strategy for calibration of MALDI-TOF PMF spectra that makes use of the phenomenon of peptide mass clustering, and enables spectrum calibration prior to the step of database interrogation, before or after peak extraction. Typically, mass errors are reduced by 40-60%. Accuracy improvement at this early stage can help avoid losing protein candidates, reduce the number of external calibration spots, eliminate internal calibrants, and reduce the number of candidates being scored, thereby reducing analysis time. Different variants of the method are discussed and compared to known calibration methods, such as relying on known calibrants or comparison to putative database candidates. In order to allow precise description of the method and to place the results in perspective, theoretical considerations of peptide databases and scoring functions are also discussed.
Blocking conformational changes in biologically active proteins holds therapeutic promise. Inspired by the susceptibility of viral entry to inhibition by synthetic peptides that block the formation of helixhelix interactions in viral envelope proteins, we developed a computational approach for predicting interacting helices. Using this approach, which combines correlated mutations analysis and Fourier transform, we designed peptides that target gp96 and clusterin, 2 secreted chaperones known to shift between inactive and active conformations. In human blood mononuclear cells, the gp96-derived peptide inhibited the production of TNF␣, IL-1, IL-6, and IL-8 induced by endotoxin by >80%. When injected into mice, the peptide reduced circulating levels of endotoxin-induced TNF␣, IL-6, and IFN␥ by >50%. The clusterin-derived peptide arrested proliferation of several neoplastic cell lines, and significantly enhanced the cytostatic activity of taxol in vitro and in a xenograft model of lung cancer. Also, the predicted mode of action of the active peptides was experimentally verified. Both peptides bound to their parent proteins, and their biological activity was abolished in the presence of the peptides corresponding to the counterpart helices. These data demonstrate a previously uncharacterized method for rational design of protein antagonists.cancer ͉ contact map prediction ͉ cytokines ͉ inflammation ͉ helix C onformational changes in proteins have an essential role in regulating activity. Natural and synthetic molecules that modulate such changes are of considerable biological importance. Such molecules include allosteric effectors that alter the rate of enzymecatalyzed reactions (1), molecules that shift the oligomerization equilibrium of proteins (2), and molecules that interfere with transmembrane helix-helix associations (3).Conformational changes that have been extensively studied are those that take place during viral-induced membrane fusion. This process is required for the propagation of enveloped viruses, and is facilitated by viral encoded type 1 integral membrane proteins (4, 5). Viral entry of enveloped viruses depends on a conformational change involving the formation of helix-helix interactions, i.e., 2 alpha helices that do not interact in the native (nonfusogenic) state, but do interact with each other when the protein folds into its fusion-active (fusogenic) form. Remarkably, synthetic peptides corresponding to some of these helical segments have an antiviral activity (6 -8), of which one has been developed for the treatment of HIV-1 infection (9, 10).We hypothesized that such a mode of inhibition could be also applied on nonviral proteins. The aim of the present study was to develop a computational tool for the detection of intramolecular helix-helix interactions and to use this tool for detecting such interacting helices in proteins of interest. This study focuses on secreted chaperones due to their biological and therapeutic relevance (11-14), and because conformational changes are known to take p...
TwinPeaks, a close variant of the SEQUEST protein identification algorithm, is capable of unrestricted, large-scale, identification of post-translation modifications (PTMs). TwinPeaks is applied on a sample of 100441 tandem mass spectra from the HUPO Plasma Proteome Project data set, with full non-redundant human as a reference protein database. With a 3.5% error rate, TwinPeaks identifies a collection of 539 spectra that were not identified by the usual PTM-restricted identification algorithm. At this error rate, TwinPeaks increases the rate of spectra identifications by at least 17.6%, making unrestricted PTM identification an integral part of proteomics.
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