Statistical identification of differentially labeled peptides from liquid chromatography tandem mass spectrometry

LC-MS/MS with certain labeling techniques such as isotope-coded affinity tag (ICAT) enables quantitative analysis of paired protein samples. However, current identification and quantification of differentially expressed peptides (and proteins) are not reliable for large proteomics screening of complex biological samples. The number of replicates is often limited because of the high cost of experiments and the limited supply of samples. Traditionally, a simple fold change cutoff is used, which results in a high rate of false positives. Standard statistical methods such as the two-sample t-test are unreliable and severely underpowered due to high variability in LC-MS/MS data, especially when only a small number of replicates are available. Using an advanced error pooling technique, we propose a novel statistical method that can reliably identify differentially expressed proteins while maintaining a high sensitivity, particularly with a small number of replicates. The proposed method was applied both to an extensive simulation study and a proteomics comparison between microparticles (MPs) generated from platelet (platelet MPs) and MPs isolated from plasma (plasma MPs). In these studies, we show a significant improvement of our statistical analysis in the identification of proteins that are differentially expressed but not detected by other statistical methods. In particular, several important proteins - two peptides for beta-globin and three peptides for von Willebrand Factor (vWF) - were identified with very small false discovery rates (FDRs) by our method, while none was significant when other conventional methods were used. These proteins have been reported with their important roles in microparticles in human blood cells: vWF is a platelet and endothelial cell product that binds to P-selectin, GP1b, and GP IIb/IIIa, and beta-globin is one of the peptides of hemoglobin involved in the transportation of oxygen by red blood cells.

Autologous transplantation of muscle-derived CD133+ stem cells in Duchenne muscle patients

Duchenne muscular dystrophy (DMD) is a lethal X-linked recessive muscle disease due to defect on the gene encoding dystrophin. The lack of a functional dystrophin in muscles results in the fragility of the muscle fiber membrane with progressive muscle weakness and premature death. There is no cure for DMD and current treatment options focus primarily on respiratory assistance, comfort care, and delaying the loss of ambulation. Recent works support the idea that stem cells can contribute to muscle repair as well as to replenishment of the satellite cell pool. Here we tested the safety of autologous transplantation of muscle-derived CD133+ cells in eight boys with Duchenne muscular dystrophy in a 7-month, double-blind phase I clinical trial. Stem cell safety was tested by measuring muscle strength and evaluating muscle structures with MRI and histological analysis. Timed cardiac and pulmonary function tests were secondary outcome measures. No local or systemic side effects were observed in all treated DMD patients. Treated patients had an increased ratio of capillary per muscle fibers with a switch from slow to fast myosin-positive myofibers.

Dragon method for finding novel tyrosinase inhibitors: Biosilico identification and experimental in vitro assays

QSAR (quantitative structure-activity relationship) studies of tyrosinase inhibitors employing Dragon descriptors and linear discriminant analysis (LDA) are presented here. A data set of 653 compounds, 245 with tyrosinase inhibitory activity and 408 having other clinical uses were used. The active data set was processed by k-means cluster analysis in order to design training and prediction series. Seven LDA-based QSAR models were obtained. The discriminant functions applied showed a globally good classification of 99.79% for the best model Class=-96.067+1.988 x 10(2)X0Av +9 1.907 BIC3 + 6.853 CIC1 in the training set. External validation processes to assess the robustness and predictive power of the obtained model were carried out. This external prediction set had an accuracy of 99.44%. After that, the developed models were used in ligand-based virtual screening of tyrosinase inhibitors from the literature and never considered in either training or predicting series. In this case, all screened chemicals were correctly classified by the LDA-based QSAR models. As a final point, these fitted models were used in the screening of new bipiperidine series as new tyrosinase inhibitors. These methods are an adequate alternative to the process of selection/identification of new bioactive compounds. The biosilico assays and in vitro results of inhibitory activity on mushroom tyrosinase showed good correspondence. It is important to stand out that compound BP4 (IC(50)=1.72 microM) showed higher activity in the inhibition against the enzyme than reference compound kojic acid (IC(50)=16.67 microM) and l-mimosine (IC(50)=3.68 microM). These results support the role of biosilico algorithm for the identification of new tyrosinase inhibitor compounds.

Drosophila as a model system for antibacterial peptides

As a defence against bacteria, infected insects synthesize cecropins and a large number of other bactericidal proteins and peptides. To understand this response and its possible relationship with similar systems in mammals, we need to characterize the induced components and how they act, as well as how this antibacterial response is initiated. To study the molecular basis for this response we cloned the genes for cecropins and other bactericidal peptides from Drosophila, 14 genes in total. The cecropin genes were selected as convenient markers for the immune response because they are strongly induced by different microbial substances. In contrast the lysozyme gene family is constitutively expressed in the digestive tract. We have developed an inducible blood cell line from Drosophila for studying the immune response in vitro. Using this system we are now investigating the function of membrane proteins and signal pathways in the transcriptional activation of immune genes in Drosophila.

A collision cross-section database of singly-charged peptide ions

A database of ion-neutral collision cross-sections for singly-charged peptide ions is presented. The peptides included in the database were generated by enzymatic digestion of known proteins using three different enzymes, resulting in peptides that differ in terms of amino acid composition as well as N-terminal and C-terminal residues. The ion-neutral collision cross-sections were measured using ion mobility (IM) spectrometry that is directly coupled to a time-of-flight (TOF) mass spectrometer. The ions were formed by a matrix-assisted laser desorption ionization (MALDI) ion source operated at pressures (He bath gas) of 2 to 3 torr. The majority (63%) of the peptide ion collision cross-sections correlate well with structures that are best described as charge-solvated globules, but a significant number of the peptide ions exhibit collision cross-sections that are significantly larger or smaller than the average, globular mobility-mass correlation. Of the peptide ions having larger than average collision cross-sections, approximately 71% are derived from trypsin digestion (C-terminal Arg or Lys residues) and most of the peptide ions that have smaller (than globular) collision cross-sections are derived from pepsin digestion (90%).

The Bogorol family of antibiotics: template-based structure elucidation and a new approach to positioning enantiomeric pairs of amino acids

The sequence positions of d and l Leu and Lys residues in bogorol A (1) have been defined by a simple and novel approach that utilizes small amounts of sample and focuses on detecting the order in which amino acids are liberated from the parent peptide during acid-catalyzed hydrolysis. This technique builds on a previously established relationship between the steric and electronic features of amino acids and their predilection for acidic liberation from polypeptides via dipeptides. The results, which complete the structure of bogorol A, have been confirmed by traditional degradation experiments. Utilizing the knowledge of the structure of bogorol A (1) as a template, we rapidly elucidated the structures of bogorols B-E (2-5) via analysis of ESI-MS and ESI-MS/MS data and GC analysis of degradation products. The bogorol cationic peptide antibiotics contain a number of unusual structural features, which include the reduction of the C-terminal residue to valinol, an N-terminal residue of 2-hydroxy-3-methylpentanoic acid, the incorporation of four d amino acids, and the presence of a dehydroamino acid. Bogorols show selective and relatively potent activity against methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus spp., as well as moderate activity against Escherichia coli.

Proteomic and peptidomic characterization of the venom from the Chinese bird spider, Ornithoctonus huwena Wang

The bird spider Ornithoctonus huwena Wang is a very venomous spider in China. Several compounds with different types of biological activities have been identified previously from the venom of this spider. In this study, we have performed a proteomic and peptidomic analysis of the venom. The venom was preseparated into two parts: the venom proteins with molecular weight (MW) higher than 10,000 and the venom peptides with MW lower than 10 000. Using one-dimensional gel electrophoresis (1-DE), two-dimensional gel electrophoresis (2-DE), and mass spectrometry, 90 proteins were identified, including some important enzymes, binding proteins, and some proteins with significant biological functions. For venom peptides, a combination of cation-exchange and reversed-phase chromatography was employed. More than 100 components were detected by mass spectrometry, and 47 peptides were sequenced by Edman degradation. The peptides display structural and pharmacological diversity and share little sequence similarity with peptides from other animal venoms, which indicates the venom of O. huwena Wang is unique. The venom peptides can be classified into several superfamilies. Also it is revealed that gene duplication and focal hypermutation have taken place during the evolution of the spider toxins.

Estimating the statistical significance of peptide identifications from shotgun proteomics experiments

We present a wrapper-based approach to estimate and control the false discovery rate for peptide identifications using the outputs from multiple commercially available MS/MS search engines. Features of the approach include the flexibility to combine output from multiple search engines with sequence and spectral derived features in a flexible classification model to produce a score associated with correct peptide identifications. This classification model score from a reversed database search is taken as the null distribution for estimating p-values and false discovery rates using a simple and established statistical procedure. Results from 10 analyses of rat sera on an LTQ-FT mass spectrometer indicate that the method is well calibrated for controlling the proportion of false positives in a set of reported peptide identifications while correctly identifying more peptides than rule-based methods using one search engine alone.

Quantification of chemical peptide reactivity for screening contact allergens: a classification tree model approach

In the interest of reducing animal use, in vitro alternatives for skin sensitization testing are under development. One unifying characteristic of chemical allergens is the requirement that they react with proteins for the effective induction of skin sensitization. The majority of chemical allergens are electrophilic and react with nucleophilic amino acids. To determine whether and to what extent reactivity correlates with skin sensitization potential, 82 chemicals comprising allergens of different potencies and nonallergenic chemicals were evaluated for their ability to react with reduced glutathione (GSH) or with two synthetic peptides containing either a single cysteine or lysine. Following a 15-min reaction time with GSH, or a 24-h reaction time with the two synthetic peptides, the samples were analyzed by high-performance liquid chromatography. UV detection was used to monitor the depletion of GSH or the peptides. The peptide reactivity data were compared with existing local lymph node assay data using recursive partitioning methodology to build a classification tree that allowed a ranking of reactivity as minimal, low, moderate, and high. Generally, nonallergens and weak allergens demonstrated minimal to low peptide reactivity, whereas moderate to extremely potent allergens displayed moderate to high peptide reactivity. Classifying minimal reactivity as nonsensitizers and low, moderate, and high reactivity as sensitizers, it was determined that a model based on cysteine and lysine gave a prediction accuracy of 89%. The results of these investigations reveal that measurement of peptide reactivity has considerable potential utility as a screening approach for skin sensitization testing, and thereby for reducing reliance on animal-based test methods.

Novel families of toxin-like peptides in insects and mammals: a computational approach

Most animal toxins are short proteins that appear in venom and vary in sequence, structure and function. A common characteristic of many such toxins is their apparent structural stability. Sporadic instances of endogenous toxin-like proteins that function in non-venom context have been reported. We have utilized machine learning methodology, based on sequence-derived features and guided by the notion of structural stability, in order to conduct a large-scale search for toxin and toxin-like proteins. Application of the method to insect and mammalian sequences revealed novel families of toxin-like proteins. One of these proteins shows significant similarity to ion channel inhibitors that are expressed in cone snail and assassin bug venom, and is surprisingly expressed in the bee brain. A toxicity assay in which the protein was injected to fish induced a strong yet reversible paralytic effect. We suggest that the protein may function as an endogenous modulator of voltage-gated Ca(2+) channels. Additionally, we have identified a novel mammalian cluster of toxin-like proteins that are expressed in the testis. We suggest that these proteins might be involved in regulation of nicotinic acetylcholine receptors that affect the acrosome reaction and sperm motility. Finally, we highlight a possible evolutionary link between venom toxins and antibacterial proteins. We expect our methodology to enhance the discovery of additional novel protein families.

Non-metabolic membrane tubulation and permeability induced by bioactive peptides

Background

Basic cell-penetrating peptides are potential vectors for therapeutic molecules and display antimicrobial activity. The peptide-membrane contact is the first step of the sequential processes leading to peptide internalization and cell activity. However, the molecular mechanisms involved in peptide-membrane interaction are not well understood and are frequently controversial. Herein, we compared the membrane activities of six basic peptides with different size, charge density and amphipaticity: Two cell-penetrating peptides (penetratin and R9), three amphipathic peptides and the neuromodulator substance P.

Methodology/Principal Findings

Experiments of X ray diffraction, video-microscopy of giant vesicles, fluorescence spectroscopy, turbidimetry and calcein leakage from large vesicles are reported. Permeability and toxicity experiments were performed on cultured cells. The peptides showed differences in bilayer thickness perturbations, vesicles aggregation and local bending properties which form lipidic tubular structures. These structures invade the vesicle lumen in the absence of exogenous energy.

Conclusions/Significance

We showed that the degree of membrane permeabilization with amphipathic peptides is dependent on both peptide size and hydrophobic nature of the residues. We propose a model for peptide-induced membrane perturbations that explains the differences in peptide membrane activities and suggests the existence of a facilitated “physical endocytosis,” which represents a new pathway for peptide cellular internalization.

Structural correlates of antimicrobial efficacy in IL-8 and related human kinocidins

Chemokines are small (8-12 kDa) effector proteins that potentiate leukocyte chemonavigation. Beyond this role, certain chemokines have direct antimicrobial activity against human pathogenic organisms; such molecules are termed kinocidins. The current investigation was designed to explore the structure-activity basis for direct microbicidal activity of kinocidins. Amino acid sequence and 3-dimensional analyses demonstrated these molecules to contain iterations of the conserved gamma-core motif found in broad classes of classical antimicrobial peptides. Representative CXC, CC and C cysteine-motif-group kinocidins were tested for antimicrobial activity versus human pathogenic bacteria and fungi. Results demonstrate that these molecules exert direct antimicrobial activity in vitro, including antibacterial activity of native IL-8 and MCP-1, and microbicidal activity of native IL-8. To define molecular determinants governing its antimicrobial activities, the IL-8 gamma-core (IL-8gamma) and alpha-helical (IL-8alpha) motifs were compared to native IL-8 for antimicrobial efficacy in vitro. Microbicidal activity recapitulating that of native IL-8 localized to the autonomous IL-8alpha motif in vitro, and demonstrated durable microbicidal activity in human blood and blood matrices ex vivo. These results offer new insights into the modular architecture, context-related deployment and function, and evolution of host defense molecules containing gamma-core motifs and microbicidal helices associated with antimicrobial activity.

TOMOCOMD-CARDD descriptors-based virtual screening of tyrosinase inhibitors: evaluation of different classification model combinations using bond-based linear indices

A new set of bond-level molecular descriptors (bond-based linear indices) are used here in QSAR (quantitative structure-activity relationship) studies of tyrosinase inhibitors, for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones. A database of 246 compounds was collected for this study; all organic chemicals were reported as tyrosinase inhibitors; they had great structural diversity. This dataset can be considered as a helpful tool, not only for theoretical chemists but also for other researchers in this area. The set used as inactive has 412 drugs with other clinical uses. Twelve LDA-based QSAR models were obtained, the first six using the non-stochastic total and local bond-based linear indices as well as the last six ones, the stochastic molecular descriptors. The best two discriminant models computed using the non-stochastic and stochastic molecular descriptors (Eqs. , respectively) had globally good classifications of 98.95% and 89.75% in the training set, with high Matthews correlation coefficients (C) of 0.98 and 0.78. The external prediction sets had accuracies of 98.89% and 89.44%, and (C) values of 0.98 and 0.78, for models 7 and 13, respectively. A virtual screening of compounds reported in the literature with such activity was carried out, to prove the ability of present models to search for tyrosinase inhibitors, not included in the training or test set. At the end, the fitted discriminant functions were used in the selection/identification of new ethylsteroids isolated from herbal plants, looking for tyrosinase inhibitory activity. A good behavior is shown between the theoretical and experimental results on mushroom tyrosinase enzyme. It might be highlighted that all the compounds showed values under 10microM and that ES2 (IC(50)=1.25microM) showed higher activity in the inhibition against the enzyme than reference compounds kojic acid (IC(50)=16.67microM) and l-mimosine (IC(50)=3.68microM). In addition, a comparison with other established methods was carried to prove the adequate discriminatory performance of the molecular descriptors used here. The present algorithm provided useful clues that can be used to speed up in the identification of new tyrosinase inhibitor compounds.

Design, synthesis, and biological evaluation of a new class of small molecule peptide mimetics targeting the melanocortin receptors

A new bicyclic template has been developed for the synthesis of peptide mimetics. Straightforward synthetic steps, starting from amino acids, allow the facile construction of a wide range of analogs. This system was designed to target the melanocortin receptors (MCRs), with functional group selection based on a known pharmacophore and guidance from molecular modeling to rationally identify positional and stereochemical isomers likely to be active. The functions of hMCRs are critical to myriad biological activities, including pigmentation, steroidogenesis, energy homeostasis, erectile activity, and inflammation. These G-protein-coupled receptors (GPCRs) are targets for drug discovery in a number of areas, including cancer, pain, and obesity therapeutics. All compounds from this series tested to date are antagonists which bind with high affinity. Importantly, many are highly selective for a particular MCR subtype, including some of the first completely hMC5R-selective antagonists reported.

Structural congruence among membrane-active host defense polypeptides of diverse phylogeny

A requisite for efficacious host defense against pathogens and predators has prioritized evolution of effector molecules thereof. A recent multidimensional analysis of physicochemical properties revealed a novel, unifying structural signature among virtually all classes of cysteine-containing antimicrobial peptides. This motif, termed the gamma-core, is seen in host defense peptides from organisms spanning more than 2.6 billion years of evolution. Interestingly, many toxins possess the gamma-core signature, consistent with discoveries of their direct antimicrobial activity. Many microbicidal chemokines (kinocidins) likewise contain iterations of the gamma-core motif, reconciling their antimicrobial efficacy. Importantly, these polypeptide classes have evolved to target and modulate biomembranes in protecting respective hosts against unfavorable interactions with potential pathogens or predators. Extending on this concept, the current report addresses the hypothesis that antimicrobial peptides, kinocidins, and polypeptide toxins are structurally congruent and share a remarkably close phylogenetic relationship, paralleling their roles in host-pathogen relationships. Analyses of their mature amino acid sequences demonstrated that cysteine-stabilized antimicrobial peptides, kinocidins, and toxins share ancient evolutionary relatedness stemming from early precursors of the gamma-core signature. Moreover, comparative 3-D structure analysis revealed recurring iterations of antimicrobial peptide gamma-core motifs within kinocidins and toxins. However, despite such congruence in gamma-core motifs, the kinocidins diverged in overall homology from microbicidal peptides or toxins. These findings are consistent with observations that chemokines are not toxic to mammalian cells, in contrast to many antimicrobial peptides and toxins. Thus, specific functions of these molecular effectors may be governed by specific configurations of structural modules associated with a common gamma-core motif. These concepts are consistent with the hypothesis that the gamma-core is an archetype determinant in polypeptides that target or regulate with biological membranes, with specific iterations optimized to unique or cognate host defense contexts. Quantitative and qualitative data suggest these protein families emerged through both parallel and divergent processes of modular evolution. Taken together, the current and prior findings imply that the gamma-core motif contributes to conserved structures and functions of host defense polypeptides. The presence of this unifying molecular signature in otherwise diverse categories of membrane-active host defense peptides implies an ancient and essential role for such a motif in effector molecules governing host-pathogen relationships.

Selection of molecular descriptors with artificial intelligence for the understanding of HIV-1 protease peptidomimetic inhibitors-activity

Quantitative Structure Activity Relationship (QSAR) techniques are used routinely by computational chemists in drug discovery and development to analyze datasets of compounds. Quantitative numerical methods like Partial Least Squares (PLS) and Artificial Neural Networks (ANN) have been used on QSAR to establish correlations between molecular properties and bioactivity. However, ANN may be advantageous over PLS because it considers the interrelations of the modeled variables. This study focused on the HIV-1 Protease (HIV-1 Pr) inhibitors belonging to the peptidomimetic class of compounds. The main objective was to select molecular descriptors with the best predictive value for antiviral potency (Ki). PLS and ANN were used to predict Ki activity of HIV-1 Pr inhibitors and the results were compared. To address the issue of dimensionality reduction, Genetic Algorithms (GA) were used for variable selection and their performance was compared against that of ANN. Finally, the structure of the optimum ANN achieving the highest Pearson's-R coefficient was determined. On the basis of Pearson's-R, PLS and ANN were compared to determine which exhibits maximum performance. Training and validation of models was performed on 15 random split sets of the master dataset consisted of 231 compounds. For each compound 192 molecular descriptors were considered. The molecular structure and constant of inhibition (Ki) were selected from the NIAID database. Study findings suggested that non-covalent interactions such as hydrophobicity, shape and hydrogen bonding describe well the antiviral activity of the HIV-1 Pr compounds. The significance of lipophilicity and relationship to HIV-1 associated hyperlipidemia and lipodystrophy syndrome warrant further investigation.

Issues related to targeted delivery of proteins and peptides

While modern genomic and proteomic technology enables rapid screening of novel proteins and peptides as potential drug candidates, design of delivery systems for these biologics remains challenging especially to achieve site-specific pharmacological actions. This article discusses the issues associated with targeted delivery of protein and peptide drugs at physiochemical, physiological, and intracellular levels with a special focus on cancer therapy.

Mucins and TFF peptides of the tear film and lacrimal apparatus

The three-dimensional organization of the tear film, which is produced and drained by the different structures of the ocular adnexa, is essential for maintainance and protection of the ocular surface. This is facilitated by a class of large, highly glycosylated, hydrophilic glycoproteins, the mucins, which are usually expressed in association with a class of peptides having a well-defined, structurally conserved trefoil domain, the mammalian trefoil factor family (TFF) peptides. In this review, the latest information regarding mucin and TFF peptide function and regulation in the human lacrimal system, the tear film and the ocular surface is summarized with regard to mucous epithelia integrity, rheological and antimicrobial properties of the tear film and tear outflow, age-related changes and certain disease states such as dry eye, dacryostenosis and dacryolith formation.

Positive Selection on Nucleotide Substitutions and Indels in Accessory Gland Proteins of the Drosophila pseudoobscura Subgroup

Genes encoding reproductive proteins often diverge rapidly due to positive selection on nucleotide substitutions. While this general pattern is well established, the extent to which specific reproductive genes experience similar selection in different clades has been little explored, nor have possible targets of positive selection other than nucleotide substitutions, such as indels, received much attention. Here, we inspect for the signature of positive selection in the genes encoding five accessory gland proteins (Acps) (Acp26Aa, Acp32CD, Acp53Ea, Acp62F, and Acp70A) originally described from Drosophila melanogaster but with recognizable orthologues in the D. pseudoobscura subgroup. We compare patterns of selection within the D. psuedoobscura subgroup to those in the D. melanogaster subgroup. Similar patterns of positive selection were found in Acp26Aa and Acp62F in the two subgroups, while Acp53Ea and Acp70A experienced purifying selection in both subgroups. These proteins have thus remained targets for similar types of selection over long (>21-MY) periods of time. We also found several indel substitutions and polymorphisms in Acp26Aa and Acp32CD. These indels occur in the same regions as positively selected nucleotide substitutions for Acp26Aa in the D. pseudoobscura subgroup but not in the D. melanogaster subgroup. Rates of indel substitution within Acp26Aa in the D. pseudoobscura subgroup were up to several times those in noncoding regions of the Drosophila genome. This suggests that indel substitutions may be under positive selection and may play a key role in the divergence of some Acps.

A novel scoring schema for peptide identification by searching protein sequence databases using tandem mass spectrometry data

Background

Tandem mass spectrometry (MS/MS) is a powerful tool for protein identification. Although great efforts have been made in scoring the correlation between tandem mass spectra and an amino acid sequence database, improvements could be made in three aspects, including characterization ofpeaks in spectra, adoption of effective scoring functions and access to thereliability of matching between peptides and spectra.

Results

A novel scoring function is presented, along with criteria to estimate the performance confidence of the function. Through learning the typesof product ions and the probability of generating them, a hypothetic spectrum was generated for each candidate peptide. Then relative entropy was introduced to measure the similarity between the hypothetic and the observed spectra. Based on the extreme value distribution (EVD) theory, a threshold was chosen to distinguish a true peptide assignment from a random one. Tests on a public MS/MS dataset demonstrated that this method performs better than the well-known SEQUEST.

Conclusion

A reliable identification of proteins from the spectra promises a more efficient application of tandem mass spectrometry to proteomes with high complexity.

International Union of Pharmacology LVII: recommendations for the nomenclature of receptors for relaxin family peptides

Although the hormone relaxin was discovered 80 years ago, only in the past 5 years have the receptors for relaxin and three other receptors that respond to related peptides been identified with all four receptors being G-protein-coupled receptors. In this review it is suggested that the receptors for relaxin (LGR7) and those for the related peptides insulin-like peptide 3 (LGR8), relaxin-3 (GPCR135), and insulin-like peptide 5 (LGPCR142) be named the relaxin family peptide receptors 1 through 4 (RXFP1-4). RXFP1 and RXFP2 are leucine-rich repeat-containing G-protein-coupled receptors with complex binding characteristics involving both the large ectodomain and the transmembrane loops. RXFP1 activates adenylate cyclase, protein kinase A, protein kinase C, phosphatidylinositol 3-kinase, and extracellular signaling regulated kinase (Erk1/2) and also interacts with nitric oxide signaling. RXFP2 activates adenylate cyclase in recombinant systems, but physiological responses are sensitive to pertussis toxin. RXFP3 and RXFP4 resemble more conventional peptide liganded receptors and both inhibit adenylate cyclase, and in addition RXFP3 activates Erk1/2 signaling. Physiological studies and examination of the phenotypes of transgenic mice have established that relaxin has roles as a reproductive hormone involved in uterine relaxation (some species), reproductive tissue growth, and collagen remodeling but also in the cardiovascular and renal systems and in the brain. The connective tissue remodeling properties of relaxin acting at RXFP1 receptors have potential for the development of agents effective for the treatment of cardiac and renal fibrosis, asthma, and scleroderma and for orthodontic remodelling. Agents acting at RXFP2 receptors may be useful for the treatment of cryptorchidism and infertility, whereas antagonists may be used as contraceptives. The brain distribution of RXFP3 receptors suggests that actions at these receptors have the potential for the development of antianxiety and antiobesity drugs.

Antimicrobial Peptides with Unusual Amino Acid Compositions and Unusual Structures

Antimicrobial peptides, which constitute an important component of innate immunity in animal and plant kingdom, are ubiquitously distributed in nature. However, they differ widely in their sizes, sequences and structures. On the basis of their structure they have been broadly classified into three classes: a) linear peptides with propensity for amphiphilic alpha-helical structure, b) peptides with beta or alphabeta structure stabilized by different number of disulfide bridges and c) peptides with over-representation of certain amino acids or unusual structures. Although considerable amount of work has been done on peptides of all the three classes, recent reviews have emphasized on peptides belonging to the first two classes. The present review focuses on the peptides belonging to the third group. The antimicrobial peptides discussed in this article include aromatic amino acid-rich peptides, (Pro-Arg)-rich peptides, unusual defensins and defensin-like molecules, unusual antimicrobial peptides from amphibians, bacteriocins with unusual structure and anionic antimicrobial peptides.

A novel bacteriocin, thuricin 17, produced by plant growth promoting rhizobacteria strain Bacillus thuringiensis NEB17: isolation and classification

AIMS

The aim of this study was to identify and characterize a compound produced by the plant growth promoting bacterium, Bacillus thuringiensis non-Bradyrhizobium Endophytic Bacterium 17.

METHODS AND RESULTS

The bacterial peptide was analysed and purified via HPLC. Using the disk diffusion assay this peptide inhibited the growth of 16/19 B. thuringiensis strains, 4/4 Bacillus cereus strains, among others, as well as a Gram-negative strain Escherichia coli MM294 (pBS42). Both bactericidal and bacteristatic effects were observed on B. cereus ATCC 14579 and bactericidal effects were observed on B. thuringiensis ssp. thuringiensis Bt1267. The molecular weight of the peptide was estimated via SDS-PAGE and confirmed with Matrix Assisted Laser Desorption Ionization Quadrapole Time of Flight mass spectrometry; its weight is 3162 Da. The peptide is biologically active after exposure to 100 degrees C for 15 min, and within the pH range 1.00-9.25. Its activity disappeared when treated with proteinase K and protease, but not with alpha-amylase or catalase.

CONCLUSIONS

We conclude that this is the first report of a bacteriocin produced by a plant growth promoting rhizobacteria (B. thuringiensis) species and have named the bacteriocin thuricin 17.

SIGNIFICANCE AND IMPACT OF THE STUDY

Our work has characterized a bacteriocin produced by a plant growth promoting bacterium. This strain is previously reported to increase soya bean nodulation.

SwePep, a database designed for endogenous peptides and mass spectrometry

A new database, SwePep, specifically designed for endogenous peptides, has been constructed to significantly speed up the identification process from complex tissue samples utilizing mass spectrometry. In the identification process the experimental peptide masses are compared with the peptide masses stored in the database both with and without possible post-translational modifications. This intermediate identification step is fast and singles out peptides that are potential endogenous peptides and can later be confirmed with tandem mass spectrometry data. Successful applications of this methodology are presented. The SwePep database is a relational database developed using MySql and Java. The database contains 4180 annotated endogenous peptides from different tissues originating from 394 different species as well as 50 novel peptides from brain tissue identified in our laboratory. Information about the peptides, including mass, isoelectric point, sequence, and precursor protein, is also stored in the database. This new approach holds great potential for removing the bottleneck that occurs during the identification process in the field of peptidomics. The SwePep database is available to the public.

Ramifications of impaired PRPP synthesis in Saccharomyces cerevisiae

The model eukaryote Saccharomyces cerevisiae is well suited to investigate the causes of metabolic disturbance. PRPP [5-phospho-D-ribosyl-1(alpha)-pyrophosphate] may be regarded as a junction of carbon and nitrogen metabolism. As a result of this central position, perturbations in its synthesis can give rise to many unexpected cellular events, such as impaired cell integrity. We have taken advantage of S. cerevisiae's genetic tractability to investigate the metabolic links responsible for connecting the biochemical intermediate PRPP to apparently unrelated cellular functions. This approach provides insight into the co-ordination of different biological processes.