Identification of Potential Auxin-Responsive Small Signaling Peptides through a Peptidomics Approach in Arabidopsis thaliana.

Small signaling peptides (SSPs) are a class of short peptides playing critical roles in plant growth and development. SSPs are also involved in the phytohormone signaling pathway. However, identification of mature SSPs is still a technical challenge because of their extremely low concentrations in plant tissue and complicated interference by many other metabolites. Here, we report an optimized protocol to extract SSPs based on protoplast extraction and to analyze SSPs based on tandem mass spectrometry peptidomics. Using plant protoplasts as the material, soluble peptides were directly extracted into phosphate buffer. The interference of non-signaling peptides was significantly decreased. Moreover, we applied the protocol to identify potential SSPs in auxin treated wild type and auxin biosynthesis defective mutant yuc2yuc6. Over 100 potential SSPs showed a response to auxin in Arabidopsis thaliana.

Global pentapeptide statistics are far away from expected distributions.

The relationships between polypeptide composition, sequence, structure and function have been puzzling biologists ever since first protein sequences were determined. Here, we study the statistics of occurrence of all possible pentapeptide sequences in known proteins. To compensate for the non-uniform distribution of individual amino acid residues in protein sequences, we investigate separately all possible permutations of every given amino acid composition. For the majority of permutation groups we find that pentapeptide occurrences deviate strongly from the expected binomial distributions, and that the observed distributions are also characterized by high numbers of outlier sequences. An analysis of identified outliers shows they often contain known motifs and rare amino acids, suggesting that they represent important functional elements. We further compare the pentapeptide composition of regions known to correspond to protein domains with that of non-domain regions. We find that a substantial number of pentapeptides is clearly strongly favored in protein domains. Finally, we show that over-represented pentapeptides are significantly related to known functional motifs and to predicted ancient structural peptides.

isGPT: An optimized model to identify sub-Golgi protein types using SVM and Random Forest based feature selection.

The Golgi Apparatus (GA) is a key organelle for protein synthesis within the eukaryotic cell. The main task of GA is to modify and sort proteins for transport throughout the cell. Proteins permeate through the GA on the ER (Endoplasmic Reticulum) facing side (cis side) and depart on the other side (trans side). Based on this phenomenon, we get two types of GA proteins, namely, cis-Golgi protein and trans-Golgi protein. Any dysfunction of GA proteins can result in congenital glycosylation disorders and some other forms of difficulties that may lead to neurodegenerative and inherited diseases like diabetes, cancer and cystic fibrosis. So, the exact classification of GA proteins may contribute to drug development which will further help in medication. In this paper, we focus on building a new computational model that not only introduces easy ways to extract features from protein sequences but also optimizes classification of trans-Golgi and cis-Golgi proteins. After feature extraction, we have employed Random Forest (RF) model to rank the features based on the importance score obtained from it. After selecting the top ranked features, we have applied Support Vector Machine (SVM) to classify the sub-Golgi proteins. We have trained regression model as well as classification model and found the former to be superior. The model shows improved performance over all previous methods. As the benchmark dataset is significantly imbalanced, we have applied Synthetic Minority Over-sampling Technique (SMOTE) to the dataset to make it balanced and have conducted experiments on both versions. Our method, namely, identification of sub-Golgi Protein Types (isGPT), achieves accuracy values of 95.4%, 95.9% and 95.3% for 10-fold cross-validation test, jackknife test and independent test respectively. According to different performance metrics, isGPT performs better than state-of-the-art techniques. The source code of isGPT, along with relevant dataset and detailed experimental results, can be found at https://github.com/srautonu/isGPT.

In the picture: disulfide-poor conopeptides, a class of pharmacologically interesting compounds

During evolution, nature has embraced different strategies for species to survive. One strategy, applied by predators as diverse as snakes, scorpions, sea anemones and cone snails, is using venom to immobilize or kill a prey. This venom offers a unique and extensive source of chemical diversity as it is driven by the evolutionary pressure to improve prey capture and/or to protect their species. Cone snail venom is an example of the remarkable diversity in pharmacologically active small peptides that venoms can consist of. These venom peptides, called conopeptides, are classified into two main groups based on the number of cysteine residues, namely disulfide-rich and disulfide-poor conopeptides. Since disulfide-poor conotoxins are minor components of this venom cocktail, the number of identified peptides and the characterization of these peptides is far outclassed by its cysteine-rich equivalents. This review provides an overview of 12 families of disulfide-poor peptides identified to date as well as the state of affairs.

Proposed systematic nomenclature for orbitides.

Orbitides are short (5-11 amino acid residue), ribosomally synthesized homodetic plant cyclic peptides characterized by N-to-C amide bonds rather than disulfide bonds. Orbitides can be discovered using mass spectrometry of plant extracts or by identifying DNA sequences coding for the precursor protein. The number of orbitides that have been characterized to date, by a number of different research groups, is modest. The nomenclatural system currently used for the Type VI cyclic peptides has been developed in an ad hoc fashion and is somewhat arbitrary. We propose a systematic naming system specifically for the Type VI cyclic peptides that reflects the taxonomic name of the species producing the orbitides and a numbering system that enables systematic representation of amino acid residues and modifications. The proposed naming system emulates the IUPAC Nomenclature for Natural Products and UniProt, both of which use abbreviations of taxonomic names for the compounds in question. Nomenclature for post-translational modifications also follows the IUPAC precedent, as well as the cyclic peptide literature. Furthermore, the proposed system aims to maintain agreement with the precedents set by the pre-existing literature. An example of the proposed nomenclature is provided using the methionine-containing homodetic peptides of Linum usitatissimum (flaxseed).

On the amyloid datasets used for training PAFIG--how (not) to extend the experimental dataset of hexapeptides.

BACKGROUND: Amyloids are proteins capable of forming aberrant intramolecular contact sites, characteristic of beta zipper configuration. Amyloids can underlie serious health conditions, e.g. Alzheimer's or Parkinson's diseases. It has been proposed that short segments of amino acids can be responsible for protein amyloidogenicity, but no more than two hundred such hexapeptides have been experimentally found. The authors of the computational tool Pafig published in BMC Bioinformatics a method for extending the amyloid hexapeptide dataset that could be used for training and testing models. They assumed that all hexapeptides belonging to an amyloid protein can be regarded as amylopositive, while those from proteins never reported as amyloid are always amylonegative. Here we show why the above described method of extending datasets is wrong and discuss the reasons why the incorrect data could lead to falsely correct classification. RESULTS: The amyloid classification of hexapeptides by Pafig was confronted with the classification results from different state of the art computational methods and the outputs of all methods were studied by clustering analysis. The clustering methods show that Pafig is an outlier with regard to other approaches. Our study of the statistical patterns of its training and testing datasets showed a strong bias towards STVIIE hexapeptide in their positive part. Different statistical patterns of seemingly amylo-positive and -negative hexapeptides allow for a repeatable classification, which is not related to amyloid propensity of the hexapetides. CONCLUSIONS: Our study on recognition of amyloid hexapeptides showed that occurrence of incidental patterns in wrongly selected datasets can produce falsely correct results of classification. The assumption that all hexapeptides belonging to amyloid protein can be regarded as amylopositive and those from proteins never reported as amyloid are always amylonegative is not supported by any other computational method. This is in line with experimental observations that amyloid propensity of a full protein can result from only one amyloidogenic fragment in this protein, while the occurrence of amyliodogenic part that is well hidden inside the protein may never lead to fibril formation. This leads to the conclusion that Pafig does not provide correct classification with regard to amyloidogenicity.

Hybrid biogeography based simultaneous feature selection and MHC class I peptide binding prediction using support vector machines and random forests.

Accurate detection of peptides binding to specific Major Histocompatibility Complex Class I (MHC-I) molecules is extremely important for understanding the underlying process of the immune system, as well as for effective vaccine design and developing immunotherapies. Development of learning algorithms and their application for binding predictions have thus speeded up the state-of-the-art in immunological research, in a cost-effective manner. In this work, we propose the application of a hybrid filter-wrapper algorithm employing concepts from the recently developed biogeography based optimization algorithm, in conjunction with SVM and Random Forests for identification of MHC-I binding peptides. In the process, we demonstrate the effectiveness of this evolutionary technique, coupled with weighted heuristics, for the construction of improved prediction models. The experiments have been carried out for the CoEPrA competition datasets (accessible online at: http://www.coepra.org) and the results show a marked improvement over the winner results in some situations and comparably good with regard to others .We thus hope to initiate further research on the application of this new bio-inspired methodology for immunological research.

Rapid phylogenetic and functional classification of short genomic fragments with signature peptides.

BACKGROUND: Classification is difficult for shotgun metagenomics data from environments such as soils, where the diversity of sequences is high and where reference sequences from close relatives may not exist. Approaches based on sequence-similarity scores must deal with the confounding effects that inheritance and functional pressures exert on the relation between scores and phylogenetic distance, while approaches based on sequence alignment and tree-building are typically limited to a small fraction of gene families. We describe an approach based on finding one or more exact matches between a read and a precomputed set of peptide 10-mers. RESULTS: At even the largest phylogenetic distances, thousands of 10-mer peptide exact matches can be found between pairs of bacterial genomes. Genes that share one or more peptide 10-mers typically have high reciprocal BLAST scores. Among a set of 403 representative bacterial genomes, some 20 million 10-mer peptides were found to be shared. We assign each of these peptides as a signature of a particular node in a phylogenetic reference tree based on the RNA polymerase genes. We classify the phylogeny of a genomic fragment (e.g., read) at the most specific node on the reference tree that is consistent with the phylogeny of observed signature peptides it contains. Using both synthetic data from four newly-sequenced soil-bacterium genomes and ten real soil metagenomics data sets, we demonstrate a sensitivity and specificity comparable to that of the MEGAN metagenomics analysis package using BLASTX against the NR database. Phylogenetic and functional similarity metrics applied to real metagenomics data indicates a signal-to-noise ratio of approximately 400 for distinguishing among environments. Our method assigns ~6.6 Gbp/hr on a single CPU, compared with 25 kbp/hr for methods based on BLASTX against the NR database. CONCLUSIONS: Classification by exact matching against a precomputed list of signature peptides provides comparable results to existing techniques for reads longer than about 300 bp and does not degrade severely with shorter reads. Orders of magnitude faster than existing methods, the approach is suitable now for inclusion in analysis pipelines and appears to be extensible in several different directions.

Classification of amino acids and oligopeptides with the use of multi-mode chemical images obtained with ion selective electrode array.

The analysis of amino acids and oligopeptides as important bioanalytes is a significant task in medical diagnostics and proteomic research and currently it is based on chromatographic and electrophoretic methods. In this paper, an approach based on sensor array coupled with titration is proposed for effective recognition of 5 amino acids and 4 oligopeptides. It is shown, that the increase of information gained during measurements of sensors' signals in various pH allows for capturing more data on interaction of amino acids and oligopeptides with various polymeric membranes of potentiometric electrodes used in the array, and that leads to the lowering of classification errors in partial least squares analysis.

A novel member of the adipokinetic peptide family in a "living fossil", the ice crawler Galloisiana yuasai, is the first identified neuropeptide from the order Grylloblattodea.

This is the first report on the structural identity of a neuropeptide of the insect order Grylloblattodea. A peptide was isolated and sequenced from the retrocerebral corpora cardiaca-corpora allata complex of the ice crawler, Galloisiana yuasai. The sequence of the peptide was deduced from the multiple MS(N) electrospray mass data as that of an octapeptide: pGlu-Val-Asn-Phe-Ser-Pro-Thr-Trp amide. The retention time on reversed-phase HPLC and the CID MS(2) mass spectra of a synthetic peptide with the same primary structure were exactly the same as of the natural peptide. The sequence represents a novel peptide of the adipokinetic hormone family which contains presently 50 members. The primary structure differs in only one position to a few previously discovered AKHs. A scenario is outlined that makes it likely that the most recently discovered insect order, the Mantophasmatodea, and the Grylloblattodea are closely related.

Peptides of the adipokinetic hormone/red pigment-concentrating hormone family: a new take on biodiversity.

Peptides of the adipokinetic hormone (AKH)/red pigment-concentrating hormone (RPCH) family in insects are involved in the mobilization of stored macromolecules in the fat body by activating glycogen phosphorylase or triacylglycerol lipase to increase the levels of circulating metabolites (trehalose, diacylglycerols, and also proline) during periods of intense muscular activity. Here I review the biodiversity of these peptides and outline how the 47 known bioanalogues are distributed between the different insect orders and in which species they occur.

Electrospray ionization tandem mass spectrometric study on the effect of N-terminal beta- and gamma-carbo amino acids on fragmentation of GABA-hybrid peptides.

The fragmentations of protonated and deprotonated ions of a new class of N-blocked hybrid Boc-carbopeptides containing repeats of gamma-Caa/gammaAbu- and beta-Caa/gammaAbu- (Caa==C-linked carbo gamma(4)-/beta(3)- amino acids derived from D-xylose, gammaAbu = gamma-aminobutyric acid) have been studied using electrospray ionization (ESI) ion-trap tandem mass spectrometry (MS/MS). MS/MS of a pair of these protonated diastereomers produces distinct fragmentation of the Boc group. The formation of [M + H-56](+) corresponding to loss of isobutylene is more pronounced for Boc-NH-(R)-gamma-Caa-gammaAbu-OH (2) whereas it is of low abundance for Boc-NH-(S)-gamma-Caa-gammaAbu--OH (1). Similarly, MS(2) of [M--H](-) of 2 produces an abundant [M--H--C(CH(3))(3)OH--CO(2)](-) ion, which is absent for its diastereomeric isomer 1. From this, it can be suggested that MS/MS of N-blocked Boc-protected carbopeptides may be helpful in distinguishing the stereochemistry of the N-terminus Caa. MS(3) of [M + H-Boc + H](+) ions of peptides with a gamma-amino acid (gamma-Caa/gammaAbu) at the N-terminus produces only abundant y(n) (+) ions. On the other hand, characteristic fragmentations involving the peptide backbone (b(n) (+) and y(n) (+)) and the side chain are seen when beta-Caa is at the N-terminus of the peptides. MS(3) of the [M--H--C(CH(3))(3)OH](-) ion of peptides containing gamma-Caa/gammaAbu at the N-terminus gave y(n) (-) and [M--H--C(CH(3))(3)OH--CO(2)](-) ions, whereas the presence of beta-Caa at the N-terminus yielded predominantly [M--H--C(CH(3))(3)OH--HNCO](-). Thus, on the basis of our previous study and that presented here we propose that the fragmentation of these hybrid carbopeptides is highly influenced by the type of carbo amino acid present at the N-terminus.

Differentiation of three pairs of Boc-beta,gamma- and gamma,beta-hybrid peptides by electrospray ionization tandem mass spectrometry.

A new series of Boc-N-beta(3), gamma(4)-/gamma(4), beta(3)-isomeric hybrid peptides (containing repeats of beta(3)-Caa and gamma(4)-Caa's, Caa = C-linked carbo beta(3)-/gamma(4)-amino acids derived from D-xylose) have been differentiated by both positive and negative ion electrospray ionization (ESI) ion-trap and high resolution quadrupole time-of-flight/tandem mass spectrometry (Q-TOF MS/MS). MS(n) of protonated isomeric peptides and [M+H-Boc+H](+) produce characteristic fragmentation involving the peptide backbone, the Boc-group, and the side chain. The positional isomers are differentiated from one another by the presence of y(n)(+), b(n)(+), and other fragment ions of different m/z values. It is observed that the peptides with beta-Caa at the N-terminus produce extensive fragmentation, whereas gamma-Caa gave rise to much less fragmentation. Peptides with gamma-Caa at the N-terminus lose NH(3), whereas this process is absent for the carbopeptides with beta-Caa at the N-terminus. Two pairs of dipeptide diastereomers are clearly differentiated by the collision-induced dissociation (CID) of their protonated molecules. The loss of 2-methylprop-1-ene is more pronounced for Boc-NH-(R)-beta-Caa-(R)-gamma-Caa-OCH(3) (6) and Boc-NH-(R)-gamma-Caa-(R)-beta-Caa-OCH(3) (12), whereas it is insignificant or totally absent for its protonated diastereomeric pair Boc-NH-(S)-beta-Caa-(S)-gamma-Caa-OCH(3) (1) and Boc-NH-(S)-gamma-Caa-(S)-beta-Caa-OCH(3) (7). Further, ESI negative ion tandem mass spectrometry has also been found to be useful for differentiating these isomeric peptide acids.

Water scorpions (Heteroptera, Nepidae) and giant water bugs (Heteroptera, Belostomatidae): sources of new members of the adipokinetic hormone/red pigment-concentrating hormone family.

Two novel octapeptide members of the AKH/RPCH family have been identified from the corpora cardiaca (CC) of two species of water bugs. The giant water bug Lethocerus indicus (family: Belostomatidae) contains a peptide code-named Letin-AKH with the sequence pGlu-Val-Asn-Phe-Ser-Pro-Tyr-Trp amide, and the water scorpion Nepa cinerea (family: Nepidae) has the peptide code-named Nepci-AKH with the sequence pGlu-Leu/Ile-Asn-Phe-Ser-Ser-Gly-Trp amide. The sequences were deduced from the multiple MS(N) electrospray mass data from crude CC extracts. Synthetic peptides were made and co-elution on reversed-phase high performance liquid chromatography (RP-HPLC) with the natural peptide from crude gland extract confirmed the accuracy of the deduced sequence for Letin-AKH and demonstrated that Nepci-AKH contains a Leu residue at position 2 and not an Ile residue. A previously characterized member of the AKH/RPCH family was identified in the stick water scorpion Ranatra linearis by mass spectrometry: Grybi-AKH (pGlu-Val-Asn-Phe-Ser-Thr-Gly-Trp amide) has the same mass (919 Da) as Nepci-AKH and differs in two positions from Nepci-AKH (residues 2 and 6). The apparent function of the peptides is to achieve lipid mobilization in the species under investigation; indications for this came from conspecific bioassays using the appropriate synthetic peptides for injecting into the insects. This function is very likely linked to dispersal flight metabolism of water bugs. Swimming activity in N. cinerea also results in an increase in lipid concentration in the hemolymph.

Artificial neural network models for prediction of intestinal permeability of oligopeptides.

BACKGROUND: Oral delivery is a highly desirable property for candidate drugs under development. Computational modeling could provide a quick and inexpensive way to assess the intestinal permeability of a molecule. Although there have been several studies aimed at predicting the intestinal absorption of chemical compounds, there have been no attempts to predict intestinal permeability on the basis of peptide sequence information. To develop models for predicting the intestinal permeability of peptides, we adopted an artificial neural network as a machine-learning algorithm. The positive control data consisted of intestinal barrier-permeable peptides obtained by the peroral phage display technique, and the negative control data were prepared from random sequences. RESULTS: The capacity of our models to make appropriate predictions was validated by statistical indicators including sensitivity, specificity, enrichment curve, and the area under the receiver operating characteristic (ROC) curve (the ROC score). The training and test set statistics indicated that our models were of strikingly good quality and could discriminate between permeable and random sequences with a high level of confidence. CONCLUSION: We developed artificial neural network models to predict the intestinal permeabilities of oligopeptides on the basis of peptide sequence information. Both binary and VHSE (principal components score Vectors of Hydrophobic, Steric and Electronic properties) descriptors produced statistically significant training models; the models with simple neural network architectures showed slightly greater predictive power than those with complex ones. We anticipate that our models will be applicable to the selection of intestinal barrier-permeable peptides for generating peptide drugs or peptidomimetics.

Some aspects of the venom proteome of the Colubridae snake Philodryas olfersii revealed from a Duvernoy's (venom) gland transcriptome.

We investigated the putative toxins of Philodryas olfersii (Colubridae), a representative of a family of snakes neglected in venom studies despite their growing medical importance. Transcriptomic data of the venom gland complemented by proteomic analysis of the gland secretion revealed the presence of major toxin classes from the Viperidae family, including serine proteases, metalloproteases, C-type lectins, Crisps, and a C-type natriuretic peptide (CNP). Interestingly, the phylogenetic analysis of the CNP precursor showed it as a linker between two related precursors found in Viperidae and Elapidae snakes. We suggest that these precursors constitute a monophyletic group derived from the vertebrate CNPs.

Diversity and distribution of Microcystis (Cyanobacteria) oligopeptide chemotypes from natural communities studied by single-colony mass spectrometry.

Microcystis sp. has been recognized in recent years as a producer of a high number of secondary metabolites. Among these, peptides that are produced by the non-ribosomal peptide synthetase pathway often show bioactivity or are toxic to humans. The production of particular peptides is specific for individual Microcystis clones, allowing their characterization as chemotypes by analysing the peptidome. The authors studied the in situ diversity of peptides and chemotypes in Microcystis communities from lakes in and around Berlin, Germany, by direct analysis of individual colonies by MALDI-TOF mass spectrometry. From 165 colonies analysed a total of 46 individual peptides could be identified, 21 of which have not been described previously. For six of the new peptides the structures could be elucidated from fragment patterns, while for others only a preliminary classification could be achieved. In most colonies, two to ten individual peptides were detected. In 19 colonies, 16 of which were identified as M. wesenbergii, no peptide metabolites could be detected. The peptide data of 146 colonies were subjected to an ordination (principal components analysis). The principal components were clearly formed by the microcystin variants Mcyst-LR, -RR and -YR, anabaenopeptins B and E/F, a putative microviridin, and a new cyanopeptolin. In the resulting ordination plots most colonies were grouped into five distinct groups, while 40 colonies scattered widely outside these groups. In some cases colonies from different lakes clustered closely, indicating the presence of similar chemotypes in the respective samples. With respect to colony morphology no clear correlation between a chemotype and a morphospecies could be established, but M. aeruginosa, for example, was found to produce predominantly microcystins. In contrast, M. ichthyoblabe colonies were mostly negative for microcystins and instead produced anabaenopeptins. The number of peptides detected in a limited number of samples and the various combinations of peptides in individual Microcystis colonies highlights the immense metabolic potential and diversity of this genus.

Proteomic signatures: amino acid and oligopeptide compositions differentiate among phyla.

Availability of complete genome sequences allows in-depth comparison of single-residue and oligopeptide compositions of the corresponding proteomes. We have used principal component analysis (PCA) to study the landscape of compositional motifs across more than 70 genera from all three superkingdoms. Unexpectedly, the first two principal components clearly differentiate archaea, eubacteria, and eukaryota from each other. In particular, we contrast compositional patterns typical of the three superkingdoms and characterize differences between species and phyla, as well as among patterns shared by all compositional proteomic signatures. These species-specific patterns may even extend to subsets of the entire proteome, such as proteins pertaining to individual yeast chromosomes. We identify factors that affect compositional signatures, such as living habitat, and detect strong eukaryotic preference for homopeptides and palindromic tripeptides. We further detect oligopeptides that are either universally over- or underabundant across the whole proteomic landscape, as well as oligopeptides whose over- or underabundance is phylum- or species-specific. Finally, we report that species composition signatures preserve evolutionary memory, providing a new method to compare phylogenetic relationships among species that avoids problems of sequence alignment and ortholog detection.

Evidence for a novel gonadotropin-releasing hormone in hypothalamic and forebrain areas in songbirds.

One or more of three distinct forms of gonadotropin-releasing hormones (GnRHs), has been found in all vertebrates studied. Birds are known to contain two types of GnRH, chicken GnRH-I and -II (cGnRH-I and -II), but to date nobody has investigated the possibility of the presence of lamprey GnRH-III in birds. Thus, our objective was to investigate the presence and distribution of immunoreactive lamprey (ir-lamprey) GnRH-III in hypothalamic and forebrain areas in house sparrows (Passer domesticus) and Gambel's white-crowned sparrows (Zonotrichia leucophrys gambelii). In addition to its distribution in the CNS, we investigated whether or not exogenous lamprey GnRH-III peptide could elicit luteinizing hormone (LH) release in vivo. This study presents two novel findings: 1) The widespread presence in the central nervous system of an immunoreactive third GnRH in birds that is clearly hypophysiotropic and has gonadotropin-releasing capabilities. Intravenous injection of 100 ng lamprey-GnRH-III peptide elicited a rapid rise in circulating luteinizing hormone as compared to controls. This third GnRH, ir-lamprey GnRH-III, likely has multiple functions, as suggested by its widespread distribution. 2) Ir-lamprey GnRH-III is present in abundance in telencephalic areas, including the hippocampal formation and the song control system. In no vertebrate has a GnRH been localized in these 'higher' control regions before. The fact that ir-lamprey-GnRH-III is present in auditory processing areas (higher vocal center, or HVc, area X, caudomedial neostriatum) and song-producing areas (HVc, robust nucleus of the neostriatum, or RA) suggests a direct way in which auditory processing and song production can affect circulating gonadotropins.

Development of LC-IMS-CID-TOFMS techniques: analysis of a 256 component tetrapeptide combinatorial library.

Recent improvements in ion mobility/time-of-flight mass spectrometry techniques have made it possible to incorporate nano-flow liquid chromatography and collision induced dissociation techniques. This combination of approaches provides a new strategy for detailed characterization of complex systems--such as, combinatorial libraries. Our work uses this technology to provide a detailed analysis of a tetrapeptide library having the general form Xxx1-Xxx2-Xxx3-Xxx4 where Xxx1 = Glu, Phe, Val, Asn; Xxx2 = Glu, Phe, Val, Tyr; Xxx3 = Glu, Phe, Val, Thr; and Xxx4 = Glu, Phe, Val, Leu--a system that is expected to contain 256 different peptide sequences. The results corroborate the presence of many expected peptide sequences and indicate that some synthetic steps appear to have failed. Particularly interesting is the observation of a t-butyl protecting group on the tyrosine (Tyr) residue. It appears that most Tyr containing peptides that have this t-butyl group attached favor formation of [2M + 2H]2+ dimers, which can be readily distinguished from [M + H]+ monomers based on differences in their gas-phase mobilities. In this case, we demonstrate the use of the mobility differences between [2M + 2H]2+ and [M + H]+ ions as a signature for a failure of a synthetic step.