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PubMed2003

[A novel approach for peptide identification by tandem mass spectrometry].

High throughput scoring algorithms that are used to find the match of a tandem mass spectrum to a predicted mass spectrum of a peptide within a database have been applied in shotgun proteomics. However, these algorithms could produce a significant number of incorrect peptide identifications. Here a novel approach was developed to scoring tandem mass spectra against a peptide database, in which fragment ion probabilities, number of enzymatic termini of candidate peptides, matching quality and match pattern between experimental and theoretical spectrum were considered. Benchmarking the novel scorer on a large set of experimental MS/MS spectra, it is demonstrated that PepSearch performs significantly better than the widely used software SEQUEST. The PepSearch software is available at http://compbio.sibsnet.org/projects/pepsearch.

Databases, Protein↗
PubMed2003

Immunocytochemical and molecular data guide peptide identification by mass spectrometry: orcokinin and orcomyotropin-related peptides in the stomatogastric nervous system of several crustacean species.

In order to identify new orcokinin and orcomyotropin-related peptides in crustaceans, molecular and immunocytochemical data were combined with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). In the crayfish Procambarus clarkii, four orcokinins and an orcomyotropin-related peptide are present on the precursor. Because these peptides are highly conserved, we assumed that other species have an identical number of peptides. To identify the peptides, immunocytochemistry was used to localize the regions of the stomatogastric nervous system in which orcokinins are predominantly present. One of the regions predominantly containing orcokinins was a previously undescribed olive-shaped neuropil region within the commissural ganglia of the lobsters Homarus americanus and Homarus gammarus. MALDI-TOF MS on these regions identified peptide masses that always occur together with the known orcokinins. Seven peptide ions occurred together in the peptide massspectra of the lobsters. Mass spectrometric fragmentation by MALDI-MS post-source decay (PSD) and electrospray ionization quadrupole time-of-flight mass spectrometry (ESI Q-TOF MS) collision-induced dissociation (CID) were used in the identification of six of these masses, either as orcokinins or as orcomyotropin-related peptides and revealed three hitherto unknown peptide variants, two of which are [His13]-orcokinin ([M+H]+ = 1540.8 Da) and an orcomyotropin-related peptide FDAFTTGFGHN ([M+H]+ = 1213.5 Da). The mass of the third previously unknown orcokinin variant corresponded to that of an identified orcokinin, but PSD fragmentation did not support the suggested amino acid sequence. CID analysis allowed partial de novo sequencing of this peptide. In the crab Cancer pagurus, five orcokinins and an orcomyotropin-related peptide were unambigously identified, including the previously unknown peptide variant [Ser9-Val13]-orcokinin ([M+H]+ = 1532.8 Da).

Amino Acid Sequence↗
PubMed2006

Software for computational peptide identification from MS-MS data.

Protein identification in biological samples is an important task in drug discovery research. Protein identification is nowadays regularly performed by tandem mass spectrometry (MS-MS). Because of the difficulty of measuring intact proteins using MS-MS, typically a protein is enzymically digested into peptides and the MS-MS spectrum of each peptide is measured. Computational methods are then invoked to identify the peptides, which are later combined together to identify the protein. The most recognized peptide identification software packages can be classified into four categories: database searching, de novo sequencing, sequence tagging and consensus of multiple engines.

Databases, Protein↗
PubMed2005

Differential proteomics via probabilistic peptide identification scores.

Relative quantitation is key to enable differential proteomics and hence answer biological questions by comparing samples. Classical approaches involve stable isotope labeling with/without spiked standards. Although stable isotopes may lead to precise results, their application is not straightforward. In Proteomics, 2004, 4, 2333-2351, we proposed an approach where we summed peptide identification scores to derive a semiquantitative abundance indicator. In this study, we combine such an indicator with a statistical test to detect differentially expressed proteins. We demonstrate the effectiveness of this method by using mixtures of purified proteins and human plasma spiked with proteins at low-nanomolar concentrations. The impact of the number of repeated experiments is discussed, and we show that the statistical test we use performs well with two to three repetitions, whereas a classical t-test would require at least four repetitions to achieve the same performance. Typically, 2.5-5-fold changes are detected with 90-95% confidence in human plasma. The method is finally characterized by deriving estimates of its false positive and negative rates. This new characterization is valid for a wider class of methods such as spectrum sampling (Liu, H.; Sadygov, R. G.; Yates, J. R. III. Anal. Chem. 2004, 76, 4193-4201).

Animals↗
PubMed2004

Statistical model for large-scale peptide identification in databases from tandem mass spectra using SEQUEST.

Recent technological advances have made multidimensional peptide separation techniques coupled with tandem mass spectrometry the method of choice for high-throughput identification of proteins. Due to these advances, the development of software tools for large-scale, fully automated, unambiguous peptide identification is highly necessary. In this work, we have used as a model the nuclear proteome from Jurkat cells and present a processing algorithm that allows accurate predictions of random matching distributions, based on the two SEQUEST scores Xcorr and DeltaCn. Our method permits a very simple and precise calculation of the probabilities associated with individual peptide assignments, as well as of the false discovery rate among the peptides identified in any experiment. A further mathematical analysis demonstrates that the score distributions are highly dependent on database size and precursor mass window and suggests that the probability associated with SEQUEST scores depends on the number of candidate peptide sequences available for the search. Our results highlight the importance of adjusting the filtering criteria to discriminate between correct and incorrect peptide sequences according to the circumstances of each particular experiment.

Chromatography, Liquid↗
PubMed2005

Protein and peptide identification algorithms using MS for use in high-throughput, automated pipelines.

Current proteomics experiments can generate vast quantities of data very quickly, but this has not been matched by data analysis capabilities. Although there have been a number of recent reviews covering various aspects of peptide and protein identification methods using MS, comparisons of which methods are either the most appropriate for, or the most effective at, their proposed tasks are not readily available. As the need for high-throughput, automated peptide and protein identification systems increases, the creators of such pipelines need to be able to choose algorithms that are going to perform well both in terms of accuracy and computational efficiency. This article therefore provides a review of the currently available core algorithms for PMF, database searching using MS/MS, sequence tag searches and de novo sequencing. We also assess the relative performances of a number of these algorithms. As there is limited reporting of such information in the literature, we conclude that there is a need for the adoption of a system of standardised reporting on the performance of new peptide and protein identification algorithms, based upon freely available datasets. We go on to present our initial suggestions for the format and content of these datasets.

Algorithms↗
PubMed2001

High-throughput peptide identification from protein digests using data-dependent multiplexed tandem FTICR mass spectrometry coupled with capillary liquid chromatography.

Tandem mass spectrometry (MS/MS) plays an important role in the unambiguous identification and structural elucidation of biomolecules. In contrast to conventional MS/MS approaches for protein identification where an individual polypeptide is sequentially selected and dissociated, a multiplexed-MS/MS approach increases throughput by selecting several peptides for simultaneous dissociation using either infrared multiphoton dissociation (IRMPD) or multiple frequency sustained off-resonance irradiation (SORI) collisionally induced dissociation (CID). The high mass measurement accuracy and resolution of FTICR combined with knowledge of peptide dissociation pathways allows the fragments arising from several different parent ions to be assigned. Herein we report the application of multiplexed-MS/MS coupled with on-line separations for the identification of peptides present in complex mixtures (i.e., whole cell lysate digests). Software was developed to enable "on-the-fly" data-dependent peak selection of a subset of polypeptides from each FTICR MS acquisition. In the subsequent MS/MS acquisitions, several coeluting peptides were fragmented simultaneously using either IRMPD or SORI-CID techniques. The utility of this approach has been demonstrated using a bovine serum albumin tryptic digest separated by capillary LC where multiple peptides were readily identified in single MS/MS acquisitions. We also present initial results from multiplexed-MS/MS analysis of a D. radiodurans whole cell digest to illustrate the utility of this approach for high-throughput analysis of a bacterial proteome.

Amino Acid Sequence↗
PubMed2004

Improved peptide identification in proteomics by two consecutive stages of mass spectrometric fragmentation.

MS-based proteomics usually involves the fragmentation of tryptic peptides (tandem MS or MS(2)) and their identification by searching protein sequence databases. In ion trap instruments fragments can be further fragmented and analyzed, a process termed MS/MS/MS or MS(3). Here, we report that efficient ion capture in a linear ion trap leads to MS(3) acquisition times and spectra quality similar to those for MS(2) experiments with conventional 3D ion traps. Fragmentation of N- or C-terminal ions resulted in informative and low-background spectra, even at subfemtomol levels of peptide. Typically C-terminal ions are chosen for further fragmentation, and the MS(3) spectrum greatly constrains the C-terminal amino acids of the peptide sequence. MS(3) spectra allow resolution of ambiguities in identification, a crucial problem in proteomics. Because of the sensitivity and rapid scan rates of the linear ion trap, several MS(3) spectra per peptide can be obtained even when sequencing very complex mixtures. We calculate the probability that an experimental MS(3) spectrum originates from fragmentation of a given N- or C-terminal ion of a peptide under consideration. This MS(3) identification score can be combined with the MS(2) scores of the precursor peptide from existing search engines. When MS(3) is performed on the linear ion trap-Fourier transform mass spectrometer combination, accurate peptide masses further increase confidence in peptide identification.

Algorithms↗
PubMed2004

Impact of ion trap tandem mass spectra variability on the identification of peptides.

Peptide identification based on tandem mass spectrometry and database searching algorithms has become one of the central technologies in proteomics. At the heart of this technology is the ability to reproducibly acquire high-quality tandem mass spectra for database interrogation. The variability in tandem mass spectra generation is often assumed to be minimal, and peptide identifications are typically based on a single tandem mass spectrum. In this paper, we characterize the variance of scores derived from replicate tandem mass spectra using several database search algorithms and demonstrate the effects of spectral variability on the correct identification of peptides. We show that the variance associated with the collection of tandem mass spectra can be substantial leading to sizable errors in search algorithm scores ( approximately 5-25% RSD) and ultimately incorrect assignments. Processing strategies are discussed to minimize the impact of tandem mass spectra variability on peptide identification.

Algorithms↗
PubMed1988

C-terminal peptide identification by fast atom bombardment mass spectrometry.

A previously described technique [Rose, Simona, Offord, Prior, Otto & Thatcher (1983) Biochem. J. 215, 273-277] permits the identification of the C-terminal peptide of a protein as the only peptide that does not incorporate any 18O upon partial enzymic hydrolysis in 18O-labelled water. Formation of chemical derivatives followed by combined g.l.c.-m.s. was used in this earlier work. We now describe the isolation from protein digests, by reversed-phase h.p.l.c., of labelled and unlabelled polypeptides and their direct analysis by fast atom bombardment mass spectrometry. Under the conditions used, the 18O label is retained throughout the separation and analysis, thus permitting assignments of C-terminal peptides to be made. Enzyme-catalysed exchange of label into the terminal carboxy group was found to occur in some cases without hydrolysis of a peptide bond. This effect, which may be exploited to prepare labelled peptides, does not prevent application of the method (two separate digests must then be used). We have applied our method to the analysis of enzymic partial hydrolysates of glucagon, insulin and of several proteins produced by expression of recombinant DNA.

Chromatography, High Pressure Liquid↗
PubMedDate not supplied

Topological shape and size of peptides: identification of potential allele specific helper T cell antigenic sites.

A database of primary sequences of 28 immunogenic peptides, known to elicit T cell response, derived from five different haplotypes was compiled to identify allele specific helper T cell antigenic sites using a rule based graph-theoretical method. The prediction was based on the identification of allele specific patterns in the form of "topological shape and size" present in the peptides. Indices computed from weighted connected graph models of amino acid side chains and peptides were used in this purpose. The system was trained by 10 Ad and 10 non-Ad restricted peptide sequences, assigned actives and inactives, respectively, chosen randomly from the database, and four Ad and four non-Ad restricted sequences were kept as test peptides. This allowed the system to learn about "topological shape and size" specific for Ad restricted peptides from the differences, if any, they had with the inactive peptides in that respect. The system made 100% correct prediction for the training set peptides and misclassified only one inactive peptide of the test set. The system also identified crucial residues for lambda repressor 12-24 and insulin A-chains. This identification also shows that activity related/crucial residues could be located at varying distances from the peptide terminals. To our knowledge, the method is unique of its kind in the literature and may find application in the rational design of synthetic vaccines and other peptides of immunological importance.

Alleles↗
PubMed2006

Unique peptide identification of RNase A superfamily sequences based on reinforced merging algorithms.

Human ribonuclease A (RNaseA) superfamily consists of eight RNases with high similarity in which RNase2 and RNase3 share 76.7% identity. The evolutionary variation of RNases results in differential structures and functions of the enzymes. To distinguish the characteristics of each RNase, we developed reinforced merging algorithms (RMA) to rapidly identify the unique peptide motifs for each member of the highly conserved human RNaseA superfamily. Many motifs in RNase3 identified by RMA correlated well with the antigenic regions predicted by DNAStar. Two unique peptide motifs were experimentally confirmed to contain epitopes for monoclonal antibodies (mAbs) specifically against RNase3. Further analysis of homologous RNases in different species revealed that the unique peptide motifs were located at the correspondent positions, and one of these motifs indeed matched the epitope for a specific anti-bovine pancreatic RNaseA (bpRNaseA) antibody. Our method provides a useful tool for identification of unique peptide motifs for further experimental design. The RMA system is available and free for academic use at http://bioinfo.life.nthu.edu.tw/rma/ and http://spider.cs.ntou.edu.tw/bioinformatics/RMA.html.

Algorithms↗
PubMed1988

Processing of thyrotropin-releasing hormone prohormone (pro-TRH) generates pro-TRH-connecting peptides. Identification and characterization of prepro-TRH-(160-169) and prepro-TRH-(178-199) in the rat nervous system.

Rat thyrotropin-releasing hormone prohormone (pro-TRH) contains five separate copies of the TRH progenitor sequence: Gln-His-Pro-Gly. Each of the five sequences is flanked by pairs of basic residues and linked together by one of several predicted connecting sequences. Two of the pro-TRH-connecting peptides, prepro-TRH-(160-169) and prepro-TRH-(178-199), were detected in extracts of rat neural tissues by radioimmunoassay using antibodies directed against the corresponding synthetic probes. Endogenous prepro-TRH-(160-169) and prepro-TRH-(178-199) were purified by gel exclusion chromatography, reverse-phase high pressure liquid chromatography, and ion-exchange chromatography. Structural identification of each peptide was achieved by chromatographic comparison with synthetic standards, immunological analysis, and tryptic mapping. Equimolar amounts of these connecting fragments were observed in hypothalamus and spinal cord. Quantification of TRH in spinal cord and hypothalamus extracts revealed the presence of 4.9-6.3 mol of TRH/mol of prepro-TRH-(178-199) and 4.4-6 mol of TRH/mol of prepro-TRH-(160-169), respectively. By using the indirect immunofluorescence technique, prepro-TRH-(178-199) immunoreactive cell bodies were found in the paraventricular nucleus of the hypothalamus, and a dense plexus of immunopositive nerve terminals was observed in the external zone of the median eminence, in a distribution similar to that described for TRH. These studies demonstrate that prepro-TRH-(160-169) and prepro-TRH-(178-199) are, together with TRH, predominant storage forms of the TRH precursor in hypothalamus and spinal cord, being present in molar ratios corresponding to those expected for a nearly complete processing of the prohormone molecule. The presence of pro-TRH-connecting peptides in various brain regions, including the median eminence, suggests that these peptides might act as neuromodulators in the central nervous system and/or neuroendocrine signals at the pituitary level. In the olfactory lobes, prepro-TRH is processed differently since a C-terminally extended form of TRH, prepro-TRH-(172-199), is found as a major end product along with lower but significant amounts of prepro-TRH-(178-199) and prepro-TRH-(160-169). The striking difference in pro-TRH processing patterns among the various tissues examined suggests differential regulating mechanisms for TRH and/or TRH-related activities.

Amino Acid Sequence↗
PubMed2004

A systematical analysis of tryptic peptide identification with reverse phase liquid chromatography and electrospray ion trap mass spectrometry.

In this study we systematically analyzed the elution condition of tryptic peptides and the characteristics of identified peptides in reverse phase liquid chromatography and electrospray tandem mass spectrometry (RPLC-MS/MS) analysis. Following protein digestion with trypsin, the peptide mixture was analyzed by on-line RPLC-MS/MS. Bovine serum albumin (BSA) was used to optimize acetonitrile (ACN) elution gradient for tryptic peptides, and Cytochrome C was used to retest the gradient and the sensitivity of LC-MS/MS. The characteristics of identified peptides were also analyzed. In our experiments, the suitable ACN gradient is 5% to 30% for tryptic peptide elution and the sensitivity of LC-MS/MS is 50 fmol. Analysis of the tryptic peptides demonstrated that longer (more than 10 amino acids) and multi-charge state (+2, +3) peptides are likely to be identified, and the hydropathicity of the peptides might not be related to whether it is more likely to be identified or not. The number of identified peptides for a protein might be used to estimate its loading amount under the same sample background. Moreover, in this study the identified peptides present three types of redundancy, namely identification, charge, and sequence redundancy, which may repress low abundance protein identification.

Acetonitriles↗
PubMed2002

Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

We present a statistical model to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST. Employing the expectation maximization algorithm, the analysis learns to distinguish correct from incorrect database search results, computing probabilities that peptide assignments to spectra are correct based upon database search scores and the number of tryptic termini of peptides. Using SEQUEST search results for spectra generated from a sample of known protein components, we demonstrate that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides. This analysis makes it possible to filter large volumes of MS/MS database search results with predictable false identification error rates and can serve as a common standard by which the results of different research groups are compared.

Algorithms↗
PubMed1992

Site-directed analysis of the functional domains in the factor Xa inhibitor tick anticoagulant peptide: identification of two distinct regions that constitute the enzyme recognition sites.

Recombinant tick anticoagulant peptide (rTAP) is a highly selective inhibitor of blood coagulation factor Xa. rTAP has been characterized kinetically as a slow, tight-binding, competitive inhibitor of the enzyme. We used an approach consisting of both recombinant, site-directed mutagenesis and solid-phase chemical synthesis to generate 31 independent mutations in rTAP to identify those regions of the molecule which contribute to the specific, high-affinity binding interaction with factor Xa. Our results demonstrate that the four amino-terminal residues of rTAP constitute the primary recognition determinant necessary for the formation of the high-affinity enzyme-inhibitor complex. The Arg residue in position three is probably not interacting with the S1-specificity pocket of factor Xa in a substrate-like manner since substitution at this position with a D-Arg amino acid produced only a modest decrease in affinity (5-fold). An additional domain in the rTAP molecule located between residues 40 and 54 was identified as a probable secondary binding determinant. Interestingly, this region in rTAP shares significant amino acid sequence homology with a sequence in prothrombin immediately amino-terminal to the factor Xa cleavage site that generates meizothrombin. These observations indicate that specific segments within two different regions of the rTAP molecule contribute to the potent binding interaction between rTAP and factor Xa.

Amino Acid Sequence↗
PubMedDate not supplied

Comparison of probability and likelihood models for peptide identification from tandem mass spectrometry data.

We evaluate statistical models used in two-hypothesis tests for identifying peptides from tandem mass spectrometry data. The null hypothesis H(0), that a peptide matches a spectrum by chance, requires information on the probability of by-chance matches between peptide fragments and peaks in the spectrum. Likewise, the alternate hypothesis H(A), that the spectrum is due to a particular peptide, requires probabilities that the peptide fragments would indeed be observed if it was the causative agent. We compare models for these probabilities by determining the identification rates produced by the models using an independent data set. The initial models use different probabilities depending on fragment ion type, but uniform probabilities for each ion type across all of the labile bonds along the backbone. More sophisticated models for probabilities under both H(A) and H(0) are introduced that do not assume uniform probabilities for each ion type. In addition, the performance of these models using a standard likelihood model is compared to an information theory approach derived from the likelihood model. Also, a simple but effective model for incorporating peak intensities is described. Finally, a support-vector machine is used to discriminate between correct and incorrect identifications based on multiple characteristics of the scoring functions. The results are shown to reduce the misidentification rate significantly when compared to a benchmark cross-correlation based approach.

Databases, Protein↗
PubMed2005

Determination of partial amino acid composition from tandem mass spectra for use in peptide identification strategies.

We demonstrate a new approach to the determination of amino acid composition from tandem mass spectrometrically fragmented peptides using both experimental and simulated data. The approach has been developed to be used as a search-space filter in a protein identification pipeline with the aim of increased performance above that which could be attained by using immonium ion information. Three automated methods have been developed and tested: one based upon a simple peak traversal, in which all intense ion peaks are treated as being either a b- or y-ion using a wide mass tolerance; a second which uses a much narrower tolerance and does not perform transformations of ion peaks to the complementary type; and the unique fragments method which allows for b- or y-ion type to be inferred and corroborated using a scan of the other ions present in each peptide spectrum. The combination of these methods is shown to provide a high-accuracy set of amino acid predictions using both experimental and simulated data sets. These high quality predictions, with an accuracy of over 85%, may be used to identify peptide fragments that are hard to identify using other methods. The data simulation algorithm is also shown post priori to be a good model of noiseless tandem mass spectrometric peptide data.

Algorithms↗