Systematic comparison of a two-dimensional ion trap and a three-dimensional ion trap mass spectrometer in proteomics

The utility and advantages of the recently introduced two-dimensional quadrupole ion trap mass spectrometer in proteomics over the traditional three-dimensional ion trap mass spectrometer have not been systematically characterized. Here we rigorously compared the performance of these two platforms by using over 100,000 tandem mass spectra acquired with identical complex peptide mixtures and acquisition parameters. Specifically we compared four factors that are critical for a successful proteomic study: 1) the number of proteins identified, 2) sequence coverage or the number of peptides identified for every protein, 3) the data base matching SEQUEST X(corr) and S(p) score, and 4) the quality of the fragment ion series of peptides. We found a 4-6-fold increase in the number of peptides and proteins identified on the two-dimensional ion trap mass spectrometer as a direct result of improvement in all the other parameters examined. Interestingly more than 70% of the doubly and triply charged peptides, but not the singly charged peptides, showed better quality of fragmentation spectra on the two-dimensional ion trap. These results highlight specific advantages of the two-dimensional ion trap over the conventional three-dimensional ion traps for protein identification in proteomic experiments.     

A proteomic analysis of human cilia: identification of novel components

Cilia play an essential role in protecting the respiratory tract by providing the force necessary for mucociliary clearance. Although the major structural components of human cilia have been described, a complete understanding of cilia function and regulation will require identification and characterization of all ciliary components. Estimates from studies of Chlamydomonas flagella predict that an axoneme contains > or = 250 proteins. To identify all the components of human cilia, we have begun a comprehensive proteomic analysis of isolated ciliary axonemes. Analysis by two-dimensional (2-D) PAGE resulted in a highly reproducible 2-D map consisting of over 240 well resolved components. Individual protein spots were digested with trypsin and sequenced using liquid chromatography/tandem mass spectrometry (LC/MS/MS). Peptide matches were obtained to 38 potential ciliary proteins by this approach. To identify ciliary components not resolved by 2-D PAGE, axonemal proteins were separated on a one-dimensional gel. The gel lane was divided into 45 individual slices, each of which was analyzed by LC/MS/MS. This experiment resulted in peptide matches to an additional 110 proteins. In a third approach, preparations of isolated axonemes were digested with Lys-C, and the resulting peptides were analyzed directly by LC/MS/MS or by multidimensional LC/MS/MS, leading to the identification of a further 66 proteins. Each of the four approaches resulted in the identification of a subset of the proteins present. In total, sequence data were obtained on over 1400 peptides, and over 200 potential axonemal proteins were identified. Peptide matches were also obtained to over 200 human expressed sequence tags. As an approach to validate the mass spectrometry results, additional studies examined the expression of several identified proteins (annexin I, sperm protein Sp17, retinitis pigmentosa protein RP1) in cilia or ciliated cells. These studies represent the first proteomic analysis of the human ciliary axoneme and have identified many potentially novel components of this complex organelle.     

Extended Range Proteomic Analysis (ERPA): a new and sensitive LC-MS platform for high sequence coverage of complex proteins with extensive post-translational modifications-comprehensive analysis of beta-casein and epidermal growth factor receptor (EGFR)

We have developed a new and sensitive LC-MS platform, Extended Range Proteomic Analysis (ERPA), which is able to achieve very high sequence coverage and comprehensive characterization of post-translational modifications in complex proteins. This new platform provides advantages of both the top-down and bottom-up proteomic approaches by combining (i) digestion of the protein with an enzyme, such as Lys-C, which cuts less frequently than trypsin, leading to on average a higher molecular weight peptide size, (ii) high-performance LC separation of the resulting fragments, (iii) a new data acquisition strategy using the LTQ-FTMS, a hybrid mass spectrometer that couples a linear ion trap with a Fourier transform ion cyclotron resonance (FTICR) cell, for analysis of peptides in the range of 0.5 to 10 kDa, and (iv) new data analysis methods for assigning large peptide structures and determining the site of attachment of post-translational modifications as well as structural features from the accurate precursor mass together with MS(2) and MS(3) fragmentations. The LC retention of the Lys-C fragments is increased, relative to a tryptic digest, due to the generally greater hydrophobicity of the larger peptides, a result that is particularly important for peptides containing hydrophilic modifications such as glycosylation and phosphorylation. Furthermore, additional positively charged arginine and lysine residues in the Lys-C fragments enhance the sensitivity of the post-translationally modified phospho- and glycopeptides by at least 10-fold relative to tryptic fragments. In typical operation, the FTICR cell provides a survey scan with the high mass resolution (> 100 000) and accurate mass (<2 ppm) to characterize the higher charge-state precursor ions of the larger peptides. In parallel, the linear ion trap provides MS(2) and MS(3) fragmentation spectra, with a scan speed sufficiently fast for on-line LC-MS. Together, these data provide multiple means to determine or enhance the confidence of assignment of large or complicated peptide. Using ERPA, we demonstrate >95% sequence coverage in the analysis of two heavily phosphorylated and glycosylated proteins, beta-casein at the 50 fmole level and the epidermal growth factor receptor (EGFR) at the 1 pmole level. In summary, the combination of digestion strategy, high-performance separation, and the hybrid LTQ-FTMS instrument enables comprehensive characterization of large proteins, including posttranslational modifications.     

A robust linear regression based algorithm for automated evaluation of peptide identifications from shotgun proteomics by use of reversed-phase liquid chromatography retention time

Background  

Rejection of false positive peptide matches in database searches of shotgun proteomic experimental data is highly desirable. Several methods have been developed to use the peptide retention time as to refine and improve peptide identifications from database search algorithms. This report describes the implementation of an automated approach to reduce false positives and validate peptide matches.     

A catalogue of human saliva proteins identified by free flow electrophoresis-based peptide separation and tandem mass spectrometry

Human saliva has great potential for clinical disease diagnostics. Constructing a comprehensive catalogue of saliva proteins using proteomic approaches is a necessary first step to identifying potential protein biomarkers of disease. However, because of the challenge presented in cataloguing saliva proteins with widely varying abundance, new proteomic approaches are needed. To this end, we used a newly developed approach coupling peptide separation using free flow electrophoresis with linear ion trap tandem mass spectrometry to identify proteins in whole human saliva. We identified 437 proteins with high confidence (false positive rate below 1%), producing the largest catalogue of proteins from a single saliva sample to date and providing new information on the composition and potential diagnostic utility of this fluid. The statistically validated, transparently presented, and annotated dataset provides a model for presenting large scale proteomic data of this type, which should facilitate better dissemination and easier comparisons of proteomic datasets from future studies in saliva.     

Identification and quantification of peptides and proteins secreted from prostate epithelial cells by unbiased liquid chromatography tandem mass spectrometry using goodness of fit and analysis of variance

The proteins secreted by prostate cancer cells (PC3(AR)6) were separated by strong anion exchange chromatography, digested with trypsin and analyzed by unbiased liquid chromatography tandem mass spectrometry with an ion trap. The spectra were matched to peptides within proteins using a goodness of fit algorithm that showed a low false positive rate. The parent ions for MS/MS were randomly and independently sampled from a log-normal population and therefore could be analyzed by ANOVA. Normal distribution analysis confirmed that the parent and fragment ion intensity distributions were sampled over 99.9% of their range that was above the background noise. Arranging the ion intensity data with the identified peptide and protein sequences in structured query language (SQL) permitted the quantification of ion intensity across treatments, proteins and peptides. The intensity of 101,905 fragment ions from 1421 peptide precursors of 583 peptides from 233 proteins separated over 11 sample treatments were computed together in one ANOVA model using the statistical analysis system (SAS) prior to Tukey-Kramer honestly significant difference (HSD) testing. Thus complex mixtures of proteins were identified and quantified with a high degree of confidence using an ion trap without isotopic labels, multivariate analysis or comparing chromatographic retention times.     

Optimization and use of peptide mass measurement accuracy in shotgun proteomics

Mass spectrometers that provide high mass accuracy such as FT-ICR instruments are increasingly used in proteomic studies. Although the importance of accurately determined molecular masses for the identification of biomolecules is generally accepted, its role in the analysis of shotgun proteomic data has not been thoroughly studied. To gain insight into this role, we used a hybrid linear quadrupole ion trap/FT-ICR (LTQ FT) mass spectrometer for LC-MS/MS analysis of a highly complex peptide mixture derived from a fraction of the yeast proteome. We applied three data-dependent MS/MS acquisition methods. The FT-ICR part of the hybrid mass spectrometer was either not exploited, used only for survey MS scans, or also used for acquiring selected ion monitoring scans to optimize mass accuracy. MS/MS data were assigned with the SEQUEST algorithm, and peptide identifications were validated by estimating the number of incorrect assignments using the composite target/decoy database search strategy. We developed a simple mass calibration strategy exploiting polydimethylcyclosiloxane background ions as calibrant ions. This strategy allowed us to substantially improve mass accuracy without reducing the number of MS/MS spectra acquired in an LC-MS/MS run. The benefits of high mass accuracy were greatest for assigning MS/MS spectra with low signal-to-noise ratios and for assigning phosphopeptides. Confident peptide identification rates from these data sets could be doubled by the use of mass accuracy information. It was also shown that improving mass accuracy at a cost to the MS/MS acquisition rate substantially lowered the sensitivity of LC-MS/MS analyses. The use of FT-ICR selected ion monitoring scans to maximize mass accuracy reduced the number of protein identifications by 40%.     

CHOMPER: a bioinformatic tool for rapid validation of tandem mass spectrometry search results associated with high-throughput proteomic strategies

Current efforts aimed at developing high-throughput proteomics focus on increasing the speed of protein identification. Although improvements in sample separation, enrichment, automated handling, mass spectrometric analysis, as well as data reduction and database interrogation strategies have done much to increase the quality, quantity and efficiency of data collection, significant bottlenecks still exist. Various separation techniques have been coupled with tandem mass spectrometric (MS/MS) approaches to allow a quicker analysis of complex mixtures of proteins, especially where a high number of unambiguous protein identifications are the exception, rather than the rule. MS/MS is required to provide structural / amino acid sequence information on a peptide and thus allow protein identity to be inferred from individual peptides. Currently these spectra need to be manually validated because: (a) the potential of false positive matches i.e., protein not in database, and (b) observed fragmentation trends may not be incorporated into current MS/MS search algorithms. This validation represents a significant bottleneck associated with high-throughput proteomic strategies. We have developed CHOMPER, a software program which reduces the time required to both visualize and confirm MS/MS search results and generate post-analysis reports and protein summary tables. CHOMPER extracts the identification information from SEQUEST MS/MS search result files, reproduces both the peptide and protein identification summaries, provides a more interactive visualization of the MS/MS spectra and facilitates the direct submission of manually validated identifications to a database.     

蛋白质组研究中离子阱串联质谱数据搜库结果解释方法

基于离子阱串联质谱仪的鸟枪法是一种高通量的蛋白质鉴定方法。得到的数据一般使用软件SEQUEST搜索蛋白质序列数据库,得到肽段鉴定列表以及相应的打分。为了得到蛋白质鉴定列表,还需要进行肽段鉴定结果的过滤和假阳性率的计算,然后根据肽段鉴定结果组装蛋白质列表。这两个问题目前还没有很好地解决。对已有的方法进行总结和比较,可以给搜库结果解释方法的选择提供参考,对数据质量控制方法的改进也有所帮助。     

Validation of peptide MS/MS spectra using metabolic isotope labeling for spectral matching-based shotgun proteome analysis

We report an isotope labeling shotgun proteome analysis strategy to validate the spectrum-to-sequence assignments generated by using sequence-database searching for the construction of a more reliable MS/MS spectral library. This strategy is demonstrated in the analysis of the E. coli K12 proteome. In the workflow, E. coli cells were cultured in normal and (15)N-enriched media. The differentially labeled proteins from the cell extracts were subjected to trypsin digestion and two-dimensional liquid chromatography quadrupole time-of-flight tandem mass spectrometry (2D-LC QTOF MS/MS) analysis. The MS/MS spectra of the two samples were individually searched using Mascot against the E. coli proteome database to generate lists of peptide sequence matches. The two data sets were compared by overlaying the spectra of unlabeled and labeled matches of the same peptide sequence for validation. Two cutoff filters, one based on the number of common fragment ions and another one on the similarity of intensity patterns among the common ions, were developed and applied to the overlaid spectral pairs to reject the low quality or incorrectly assigned spectra. By examining 257,907 and 245,156 spectra acquired from the unlabeled and (15)N-labeled samples, respectively, an experimentally validated MS/MS spectral library of tryptic peptides was constructed for E. coli K12 that consisted of 9,302 unique spectra with unique sequence and charge state, representing 7,763 unique peptide sequences. This E. coli spectral library could be readily expanded, and the overall strategy should be applicable to other organisms. Even with this relatively small library, it was shown that more peptides could be identified with higher confidence using the spectral search method than by sequence-database searching.     

Characterization of a high field Orbitrap mass spectrometer for proteome analysis

The field of proteomics continues to be driven by improvements in analytical technology, notably in peptide separation, quantitative MS, and informatics. In this study, we have characterized a hybrid linear ion trap high field Orbitrap mass spectrometer (Orbitrap Elite) for proteomic applications. The very high resolution available on this instrument allows 95% of all peptide masses to be measured with sub‐ppm accuracy that in turn improves protein identification by database searching. We further confirm again that mass accuracy in tandem mass spectra is a valuable parameter for improving the success of protein identification. The new CID rapid scan type of the Orbitrap Elite achieves similar performance as higher energy collision induced dissociation fragmentation and both allow the identification of hundreds of proteins from as little as 0.1 ng of protein digest on column. The new instrument outperforms its predecessor the Orbitrap Velos by a considerable margin on each metric assessed that makes it a valuable and versatile tool for MS‐based proteomics.     

iProphet: multi-level integrative analysis of shotgun proteomic data improves peptide and protein identification rates and error estimates

The combination of tandem mass spectrometry and sequence database searching is the method of choice for the identification of peptides and the mapping of proteomes. Over the last several years, the volume of data generated in proteomic studies has increased dramatically, which challenges the computational approaches previously developed for these data. Furthermore, a multitude of search engines have been developed that identify different, overlapping subsets of the sample peptides from a particular set of tandem mass spectrometry spectra. We present iProphet, the new addition to the widely used open-source suite of proteomic data analysis tools Trans-Proteomics Pipeline. Applied in tandem with PeptideProphet, it provides more accurate representation of the multilevel nature of shotgun proteomic data. iProphet combines the evidence from multiple identifications of the same peptide sequences across different spectra, experiments, precursor ion charge states, and modified states. It also allows accurate and effective integration of the results from multiple database search engines applied to the same data. The use of iProphet in the Trans-Proteomics Pipeline increases the number of correctly identified peptides at a constant false discovery rate as compared with both PeptideProphet and another state-of-the-art tool Percolator. As the main outcome, iProphet permits the calculation of accurate posterior probabilities and false discovery rate estimates at the level of sequence identical peptide identifications, which in turn leads to more accurate probability estimates at the protein level. Fully integrated with the Trans-Proteomics Pipeline, it supports all commonly used MS instruments, search engines, and computer platforms. The performance of iProphet is demonstrated on two publicly available data sets: data from a human whole cell lysate proteome profiling experiment representative of typical proteomic data sets, and from a set of Streptococcus pyogenes experiments more representative of organism-specific composite data sets.     

Proteome profile of human breast cancer tissue generated by LC-ESI-MS/MS combined with sequential protein precipitation and solubilization

Comprehensive proteome profiling of breast cancer tissue samples is challenging, as the tissue samples contain many proteins with varying concentrations and modifications. We report an effective sample preparation strategy combined with liquid chromatography (LC) electrospray ionization (ESI) quadrupole time-of-flight (QTOF) MS/MS for proteome analysis of human breast cancer tissue. The complexity of the breast cancer tissue proteome was reduced by using protein precipitation from a tissue extract, followed by sequential protein solubilization in solvents of different solubilizing strength. The individual fractions of protein mixtures or subproteomes were subjected to trypsin digestion and the resultant peptides were separated by strong cation exchange (SCX) chromatography, followed by reversed-phase capillary LC combined with high resolution and high accuracy ESI-QTOF MS/MS. This approach identified 14407 unique peptides from 3749 different proteins based on peptide matches with scores above the threshold scores at the 95% confidence level in MASCOT database search of the acquired MS/MS spectra. The false positive rate of peptide matches was determined to be 0.95% by using the target-decoy sequence search strategy. On the basis of gene ontology categorization, the identified proteins represented a wide variety of biological functions, cellular processes, and cellular locations.     

iTRAQ reagent-based quantitative proteomic analysis on a linear ion trap mass spectrometer

For proteomic analysis using tandem mass spectrometry, linear ion trap instruments provide unsurpassed sensitivity but unreliably detect low mass peptide fragments, precluding their use with iTRAQ reagent-labeled samples. Although the popular LTQ linear ion trap supports analyzing iTRAQ reagent-labeled peptides via pulsed Q dissociation, PQD, its effectiveness remains questionable. Using a standard mixture, we found careful tuning of relative collision energy necessary for fragmenting iTRAQ reagent-labeled peptides, and increasing microscan acquisition and repeat count improves quantification but identifies somewhat fewer peptides. We developed software to calculate abundance ratios via summing reporter ion intensities across spectra matching to each protein, thereby providing maximized accuracy. Testing found that results closely corresponded between analysis using optimized LTQ-PQD settings plus our software and using a Qstar instrument. Thus, we demonstrate the effectiveness of LTQ-PQD analyzing iTRAQ reagent-labeled peptides, and provide guidelines for successful quantitative proteomic studies.     

MyriMatch: highly accurate tandem mass spectral peptide identification by multivariate hypergeometric analysis

Shotgun proteomics experiments are dependent upon database search engines to identify peptides from tandem mass spectra. Many of these algorithms score potential identifications by evaluating the number of fragment ions matched between each peptide sequence and an observed spectrum. These systems, however, generally do not distinguish between matching an intense peak and matching a minor peak. We have developed a statistical model to score peptide matches that is based upon the multivariate hypergeometric distribution. This scorer, part of the "MyriMatch" database search engine, places greater emphasis on matching intense peaks. The probability that the best match for each spectrum has occurred by random chance can be employed to separate correct matches from random ones. We evaluated this software on data sets from three different laboratories employing three different ion trap instruments. Employing a novel system for testing discrimination, we demonstrate that stratifying peaks into multiple intensity classes improves the discrimination of scoring. We compare MyriMatch results to those of Sequest and X!Tandem, revealing that it is capable of higher discrimination than either of these algorithms. When minimal peak filtering is employed, performance plummets for a scoring model that does not stratify matched peaks by intensity. On the other hand, we find that MyriMatch discrimination improves as more peaks are retained in each spectrum. MyriMatch also scales well to tandem mass spectra from high-resolution mass analyzers. These findings may indicate limitations for existing database search scorers that count matched peaks without differentiating them by intensity. This software and source code is available under Mozilla Public License at this URL: http://www.mc.vanderbilt.edu/msrc/bioinformatics/.     

Exploring skyline for both MSE‐based label‐free proteomics and HRMS quantitation of small molecules

The MS^E (where MS^E is low energy (MS) and elevated energy (E) mode of acquisition) acquisition method commercialized by Waters on its Q‐TOF instruments is regarded as a unique data‐independent fragmentation approach that improves the accuracy and dynamic range of label‐free proteomic quantitation. Due to its special format, MS^E acquisition files cannot be independently analyzed with most widely used open‐source proteomic software specialized for processing data‐dependent acquisition files. In this study, we established a workflow integrating Skyline, a popular and versatile peptide‐centric quantitation program, and a statistical tool DiffProt to fulfill MS^E‐based proteomic quantitation. Comparison with the vendor software package for analyzing targeted phosphopeptides and global proteomic datasets reveals distinct advantages of Skyline in MS^E data mining, including sensitive peak detection, flexible peptide filtering, and transparent step‐by‐step workflow. Moreover, we developed a new procedure such that Skyline MS1 filtering was extended to small molecule quantitation for the first time. This new utility of Skyline was examined in a protein–ligand interaction experiment to identify multiple chemical compounds specifically bound to NDM‐1 (where NDM is New Delhi metallo‐β‐lactamase 1), an antibiotics‐resistance target. Further improvement of the current weaknesses in Skyline MS1 filtering is expected to enhance the reliability of this powerful program in full scan‐based quantitation of both peptides and small molecules.     

Matrix-assisted laser desorption/ionization- quadrupole ion trap-time of flight mass spectrometry sequencing resolves structures of unidentified peptides obtained by in-gel tryptic digestion of haptoglobin derivatives from human plasma proteomes

Two-dimensional gel electrophoresis-separated and excised haptoglobin alpha2-chain protein spots were subjected to in-gel digestion with trypsin. Previously unassigned peptide ion signals observed in mass spectrometric fingerprinting experiments were sequenced using the matrix-assisted laser desorption/ionization-quadrupole ion trap-time of flight (MALDI-QIT-TOF) mass spectrometer and showed that the haptoglobin alpha-chain derivative under study was cleaved by trypsin unspecifically. Abundant cleavages occurred C-terminal to histidine residues at H23, H28, and H87. In addition, mild acidic hydrolysis leading to cleavage after aspartic acid residues at D13 was observed. The uninterpreted tandem mass spectrometry (MS/MS) spectrum of the peptide with ion signal at 2620.19 was submitted to database search and yielded the identification of the corresponding peptide sequence comprising amino acids (aa) aa65-87 from the haptoglobin alpha-chain protein. Also, the presence of a mixture of two tryptic peptides (mass to charge ratio m/z 1708.8; aa40-54, and aa99-113, respectively), that is caused by a tiny sequence variation between the two repeats in the haptoglobin alpha2-chain protein was resolved by MS/MS fragmentation using the MALDI-QIT-TOF mass spectrometer instrument. Advantageous features such as (i) easy parent ion creation, (ii) minimal sample consumption, and (iii) real collision induced dissociation conditions, were combined successfully to determine the amino acid sequences of the previously unassigned peptides. Hence, the novel mass spectrometric sequencing method applied here has proven effective for identification of distinct molecular protein structures.     

Integrated platform for manual and high‐throughput statistical validation of tandem mass spectra

As proteomic data sets increase in size and complexity, the necessity for database‐centric software systems able to organize, compare, and visualize all the proteomic experiments in a lab grows. We recently developed an integrated platform called high‐throughput autonomous proteomic pipeline (HTAPP) for the automated acquisition and processing of quantitative proteomic data, and integration of proteomic results with existing external protein information resources within a lab‐based relational database called PeptideDepot. Here, we introduce the peptide validation software component of this system, which combines relational database‐integrated electronic manual spectral annotation in Java with a new software tool in the R programming language for the generation of logistic regression spectral models from user‐supplied validated data sets and flexible application of these user‐generated models in automated proteomic workflows. This logistic regression spectral model uses both variables computed directly from SEQUEST output in addition to deterministic variables based on expert manual validation criteria of spectral quality. In the case of linear quadrupole ion trap (LTQ) or LTQ‐FTICR LC/MS data, our logistic spectral model outperformed both XCorr (242% more peptides identified on average) and the X!Tandem E‐value (87% more peptides identified on average) at a 1% false discovery rate estimated by decoy database approach.     

Increasing information from shotgun proteomic data by accounting for misassigned precursor ion masses

Although mass spectrometers are capable of providing high mass accuracy data, assignment of true monoisotopic precursor ion mass is complicated during data-dependent ion selection for LC-MS/MS analysis of complex mixtures. The complication arises when chromatographic peak widths for a given analyte exceed the time required to acquire a precursor ion mass spectrum. The result is that many measured monoisotopic masses are misassigned due to calculation from a single mass spectrum with poor ion statistics based on only a fraction of the total available ions for a given analyte. Such data in turn produces errors in automated database searches, where precursor m/z value is one search parameter. We propose here a postacquisition approach to correct misassigned monoisotopic m/z values that involves peak detection over the entire elution profile and correction of the precursor ion monoisotopic mass. As a result of using this approach to reprocess shotgun proteomic data we increased peptide sequence assignments by 10% while reducing the estimated false positive ratio from 1 to 0.2%. We also show that 4% of the salvaged identifications may be accounted for by correction of mixed tandem mass spectra resulting from fragmentation of multiple peptides simultaneously, a situation which we refer to as accidental CID.     

An improved method for the construction of decoy peptide MS/MS spectra suitable for the accurate estimation of false discovery rates

The relevance of libraries of annotated MS/MS spectra is growing with the amount of proteomic data generated in high-throughput experiments. These reference libraries provide a fast and accurate way to identify newly acquired MS/MS spectra. In the context of multiple hypotheses testing, the control of the number of false-positive identifications expected in the final result list by means of the calculation of the false discovery rate (FDR). In a classical sequence search where experimental MS/MS spectra are compared with the theoretical peptide spectra calculated from a sequence database, the FDR is estimated by searching randomized or decoy sequence databases. Despite on-going discussion on how exactly the FDR has to be calculated, this method is widely accepted in the proteomic community. Recently, similar approaches to control the FDR of spectrum library searches were discussed. We present in this paper a detailed analysis of the similarity between spectra of distinct peptides to set the basis of our own solution for decoy library creation (DeLiberator). It differs from the previously published results in some key points, mainly in implementing new methods that prevent decoy spectra from being too similar to the original library spectra while keeping important features of real MS/MS spectra. Using different proteomic data sets and library creation methods, we evaluate our approach and compare it with alternative methods.