Combining mass spectrometry and machine learning to discover bioactive peptides.

Peptides play important roles in regulating biological processes and form the basis of a multiplicity of therapeutic drugs. To date, only about 300 peptides in human have confirmed bioactivity, although tens of thousands have been reported in the literature. The majority of these are inactive degradation products of endogenous proteins and peptides, presenting a needle-in-a-haystack problem of identifying the most promising candidate peptides from large-scale peptidomics experiments to test for bioactivity. To address this challenge, we conducted a comprehensive analysis of the mammalian peptidome across seven tissues in four different mouse strains and used the data to train a machine learning model that predicts hundreds of peptide candidates based on patterns in the mass spectrometry data. We provide in silico validation examples and experimental confirmation of bioactivity for two peptides, demonstrating the utility of this resource for discovering lead peptides for further characterization and therapeutic development.

GHB analogs confer neuroprotection through specific interaction with the CaMKIIα hub domain.

Ca2+/calmodulin-dependent protein kinase II alpha subunit (CaMKIIα) is a key neuronal signaling protein and an emerging drug target. The central hub domain regulates the activity of CaMKIIα by organizing the holoenzyme complex into functional oligomers, yet pharmacological modulation of the hub domain has never been demonstrated. Here, using a combination of photoaffinity labeling and chemical proteomics, we show that compounds related to the natural substance γ-hydroxybutyrate (GHB) bind selectively to CaMKIIα. By means of a 2.2-Å x-ray crystal structure of ligand-bound CaMKIIα hub, we reveal the molecular details of the binding site deep within the hub. Furthermore, we show that binding of GHB and related analogs to this site promotes concentration-dependent increases in hub thermal stability believed to alter holoenzyme functionality. Selectively under states of pathological CaMKIIα activation, hub ligands provide a significant and sustained neuroprotection, which is both time and dose dependent. This is demonstrated in neurons exposed to excitotoxicity and in a mouse model of cerebral ischemia with the selective GHB analog, HOCPCA (3-hydroxycyclopent-1-enecarboxylic acid). Together, our results indicate a hitherto unknown mechanism for neuroprotection by a highly specific and unforeseen interaction between the CaMKIIα hub domain and small molecule brain-penetrant GHB analogs. This establishes GHB analogs as powerful tools for investigating CaMKII neuropharmacology in general and as potential therapeutic compounds for cerebral ischemia in particular.

ProAlanase is an Effective Alternative to Trypsin for Proteomics Applications and Disulfide Bond Mapping.

Trypsin is the protease of choice in bottom-up proteomics. However, its application can be limited by the amino acid composition of target proteins and the pH of the digestion solution. In this study we characterize ProAlanase, a protease from the fungus Aspergillus niger that cleaves primarily on the C-terminal side of proline and alanine residues. ProAlanase achieves high proteolytic activity and specificity when digestion is carried out at acidic pH (1.5) for relatively short (2 h) time periods. To elucidate the potential of ProAlanase in proteomics applications, we conducted a series of investigations comprising comparative multi-enzymatic profiling of a human cell line proteome, histone PTM analysis, ancient bone protein identification, phosphosite mapping and de novo sequencing of a proline-rich protein and disulfide bond mapping in mAb. The results demonstrate that ProAlanase is highly suitable for proteomics analysis of the arginine- and lysine-rich histones, enabling high sequence coverage of multiple histone family members. It also facilitates an efficient digestion of bone collagen thanks to the cleavage at the C terminus of hydroxyproline which is highly prevalent in collagen. This allows to identify complementary proteins in ProAlanase- and trypsin-digested ancient bone samples, as well as to increase sequence coverage of noncollagenous proteins. Moreover, digestion with ProAlanase improves protein sequence coverage and phosphosite localization for the proline-rich protein Notch3 intracellular domain (N3ICD). Furthermore, we achieve a nearly complete coverage of N3ICD protein by de novo sequencing using the combination of ProAlanase and tryptic peptides. Finally, we demonstrate that ProAlanase is efficient in disulfide bond mapping, showing high coverage of disulfide-containing regions in a nonreduced mAb.

Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition without the need for spectral libraries.

Quantitative phosphoproteomics has transformed investigations of cell signaling, but it remains challenging to scale the technology for high-throughput analyses. Here we report a rapid and reproducible approach to analyze hundreds of phosphoproteomes using data-independent acquisition (DIA) with an accurate site localization score incorporated into Spectronaut. DIA-based phosphoproteomics achieves an order of magnitude broader dynamic range, higher reproducibility of identification, and improved sensitivity and accuracy of quantification compared to state-of-the-art data-dependent acquisition (DDA)-based phosphoproteomics. Notably, direct DIA without the need of spectral libraries performs close to analyses using project-specific libraries, quantifying > 20,000 phosphopeptides in 15 min single-shot LC-MS analysis per condition. Adaptation of a 3D multiple regression model-based algorithm enables global determination of phosphorylation site stoichiometry in DIA. Scalability of the DIA approach is demonstrated by systematically analyzing the effects of thirty kinase inhibitors in context of epidermal growth factor (EGF) signaling showing that specific protein kinases mediate EGF-dependent phospho-regulation.

Oncogenic Mutations Rewire Signaling Pathways by Switching Protein Recruitment to Phosphotyrosine Sites.

Tyrosine phosphorylation regulates multi-layered signaling networks with broad implications in (patho)physiology, but high-throughput methods for functional annotation of phosphotyrosine sites are lacking. To decipher phosphotyrosine signaling directly in tissue samples, we developed a mass-spectrometry-based interaction proteomics approach. We measured the in vivo EGF-dependent signaling network in lung tissue quantifying >1,000 phosphotyrosine sites. To assign function to all EGF-regulated sites, we determined their recruited protein signaling complexes in lung tissue by interaction proteomics. We demonstrated how mutations near tyrosine residues introduce molecular switches that rewire cancer signaling networks, and we revealed oncogenic properties of such a lung cancer EGFR mutant. To demonstrate the scalability of the approach, we performed >1,000 phosphopeptide pulldowns and analyzed them by rapid mass spectrometric analysis, revealing tissue-specific differences in interactors. Our approach is a general strategy for functional annotation of phosphorylation sites in tissues, enabling in-depth mechanistic insights into oncogenic rewiring of signaling networks.

Early Pleistocene enamel proteome from Dmanisi resolves Stephanorhinus phylogeny.

The sequencing of ancient DNA has enabled the reconstruction of speciation, migration and admixture events for extinct taxa1. However, the irreversible post-mortem degradation2 of ancient DNA has so far limited its recovery-outside permafrost areas-to specimens that are not older than approximately 0.5 million years (Myr)3. By contrast, tandem mass spectrometry has enabled the sequencing of approximately 1.5-Myr-old collagen type I4, and suggested the presence of protein residues in fossils of the Cretaceous period5-although with limited phylogenetic use6. In the absence of molecular evidence, the speciation of several extinct species of the Early and Middle Pleistocene epoch remains contentious. Here we address the phylogenetic relationships of the Eurasian Rhinocerotidae of the Pleistocene epoch7-9, using the proteome of dental enamel from a Stephanorhinus tooth that is approximately 1.77-Myr old, recovered from the archaeological site of Dmanisi (South Caucasus, Georgia)10. Molecular phylogenetic analyses place this Stephanorhinus as a sister group to the clade formed by the woolly rhinoceros (Coelodonta antiquitatis) and Merck's rhinoceros (Stephanorhinus kirchbergensis). We show that Coelodonta evolved from an early Stephanorhinus lineage, and that this latter genus includes at least two distinct evolutionary lines. The genus Stephanorhinus is therefore currently paraphyletic, and its systematic revision is needed. We demonstrate that sequencing the proteome of Early Pleistocene dental enamel overcomes the limitations of phylogenetic inference based on ancient collagen or DNA. Our approach also provides additional information about the sex and taxonomic assignment of other specimens from Dmanisi. Our findings reveal that proteomic investigation of ancient dental enamel-which is the hardest tissue in vertebrates11, and is highly abundant in the fossil record-can push the reconstruction of molecular evolution further back into the Early Pleistocene epoch, beyond the currently known limits of ancient DNA preservation.

Quantitative metaproteomics of medieval dental calculus reveals individual oral health status.

The composition of ancient oral microbiomes has recently become accessible owing to advanced biomolecular methods such as metagenomics and metaproteomics, but the utility of metaproteomics for such analyses is less explored. Here, we use quantitative metaproteomics to characterize the dental calculus associated with the remains of 21 humans retrieved during the archeological excavation of the medieval (ca. 1100-1450 CE) cemetery of Tjærby, Denmark. We identify 3671 protein groups, covering 220 bacterial species and 81 genera across all medieval samples. The metaproteome profiles of bacterial and human proteins suggest two distinct groups of archeological remains corresponding to health-predisposed and oral disease-susceptible individuals, which is supported by comparison to the calculus metaproteomes of healthy living individuals. Notably, the groupings identified by metaproteomics are not apparent from the bioarchaeological analysis, illustrating that quantitative metaproteomics has the potential to provide additional levels of molecular information about the oral health status of individuals from archeological contexts.

Limits for Resolving Isobaric Tandem Mass Tag Reporter Ions Using Phase-Constrained Spectrum Deconvolution.

A popular method for peptide quantification relies on isobaric labeling such as tandem mass tags (TMT), which enables multiplexed proteome analyses. Quantification is achieved by reporter ions generated by fragmentation in a tandem mass spectrometer. However, with higher degrees of multiplexing, the smaller mass differences between the reporter ions increase the mass resolving power requirements. This contrasts with faster peptide sequencing capabilities enabled by lowered mass resolution on Orbitrap instruments. It is therefore important to determine the mass resolution limits for highly multiplexed quantification when maximizing proteome depth. Here, we defined the lower boundaries for resolving TMT reporter ions with 0.0063 Da mass differences using an ultra-high-field Orbitrap mass spectrometer. We found the optimal method depends on the relative ratio between closely spaced reporter ions and that 64 ms transient acquisition time provided sufficient resolving power for separating TMT reporter ions with absolute ratio changes up to 16-fold. Furthermore, a 32 ms transient processed with phase-constrained spectrum deconvolution provides >50% more identifications with >99% quantified but with a slight loss in quantification precision and accuracy. These findings should guide decisions on what Orbitrap resolution settings to use in future proteomics experiments, relying on isobaric TMT reporter ion quantification.

UbiSite approach for comprehensive mapping of lysine and N-terminal ubiquitination sites.

Ubiquitination is a post-translational modification (PTM) that is essential for balancing numerous physiological processes. To enable delineation of protein ubiquitination at a site-specific level, we generated an antibody, denoted UbiSite, recognizing the C-terminal 13 amino acids of ubiquitin, which remain attached to modified peptides after proteolytic digestion with the endoproteinase LysC. Notably, UbiSite is specific to ubiquitin. Furthermore, besides ubiquitination on lysine residues, protein N-terminal ubiquitination is readily detected as well. By combining UbiSite enrichment with sequential LysC and trypsin digestion and high-accuracy MS, we identified over 63,000 unique ubiquitination sites on 9,200 proteins in two human cell lines. In addition to uncovering widespread involvement of this PTM in all cellular aspects, the analyses reveal an inverse association between protein N-terminal ubiquitination and acetylation, as well as a complete lack of correlation between changes in protein abundance and alterations in ubiquitination sites upon proteasome inhibition.

Generic Workflow for Mapping of Complex Disulfide Bonds Using In-Source Reduction and Extracted Ion Chromatograms from Data-Dependent Mass Spectrometry.

Disulfide bond mapping is a critical task in protein characterization as protein stability, structure, and function is dependent on correct cysteine connectivities. Mass spectrometry (MS) is the method of choice for this, providing fast and accurate characterization of simple disulfide bonds. Disulfide mapping by liquid chromatography tandem mass spectrometry (LC-MS/MS) is performed by identifying disulfide-bonded partner peptides following proteolytic digestion. With the recently introduced ability to assign complex disulfide patterns by online postcolumn partial disulfide reduction by in-source reduction (ISR) in a LC-ISR-MS/MS methodology, the main challenge is data analysis to ensure detection of both expected and unexpected disulfide species. In this study, we introduced a workflow for confident and unbiased mapping of complex disulfide bonds using the powerful combination of extracted ion chromatograms (XICs) of LC-ISR-MS/MS data. With postcolumn partial reduction, identical LC retention times of intact disulfide-bonded species, their constituting free peptides, and partially reduced variants were observed. Subsequent selective MS/MS fragmentation of all reduction products allowed confident identification of free cysteine-containing peptides using a classical shotgun proteomics database search. Matching XICs of the identified cysteine-containing peptides allowed identification of both predicted and unpredicted disulfide species, including unforeseen proteolytic specificities, missed cleavage sites, scrambled disulfide variants, and the presence of disulfide-entangled complexes. Applying this workflow, we successfully mapped the complex disulfide bonds of tertiapin and the epidermal growth factor (EGF) family members transforming growth factor α (TGFα) and EGF. In addition, we were able to characterize the disulfide patterns of the special disulfide fold of the TGFß superfamily in an all-online methodology.

Benchmarking common quantification strategies for large-scale phosphoproteomics.

Comprehensive mass spectrometry (MS)-based proteomics is now feasible, but reproducible quantification remains challenging, especially for post-translational modifications such as phosphorylation. Here, we compare the most popular quantification techniques for global phosphoproteomics: label-free quantification (LFQ), stable isotope labeling by amino acids in cell culture (SILAC) and MS2- and MS3-measured tandem mass tags (TMT). In a mixed species comparison with fixed phosphopeptide ratios, we find LFQ and SILAC to be the most accurate techniques. MS2-based TMT yields the highest precision but lowest accuracy due to ratio compression, which MS3-based TMT can partly rescue. However, MS2-based TMT outperforms MS3-based TMT when analyzing phosphoproteome changes in the DNA damage response, since its higher precision and larger identification numbers allow detection of a greater number of significantly regulated phosphopeptides. Finally, we utilize the TMT multiplexing capabilities to develop an algorithm for determining phosphorylation site stoichiometry, showing that such applications benefit from the high accuracy of MS3-based TMT.

Performance Evaluation of the Q Exactive HF-X for Shotgun Proteomics.

Progress in proteomics is mainly driven by advances in mass spectrometric (MS) technologies. Here we benchmarked the performance of the latest MS instrument in the benchtop Orbitrap series, the Q Exactive HF-X, against its predecessor for proteomics applications. A new peak-picking algorithm, a brighter ion source, and optimized ion transfers enable productive MS/MS acquisition above 40 Hz at 7500 resolution. The hardware and software improvements collectively resulted in improved peptide and protein identifications across all comparable conditions, with an increase of up to 50 percent at short LC-MS gradients, yielding identification rates of more than 1000 unique peptides per minute. Alternatively, the Q Exactive HF-X is capable of achieving the same proteome coverage as its predecessor in approximately half the gradient time or at 10-fold lower sample loads. The Q Exactive HF-X also enables rapid phosphoproteomics with routine analysis of more than 5000 phosphopeptides with short single-shot 15 min LC-MS/MS measurements, or 16 700 phosphopeptides quantified across ten conditions in six gradient hours using TMT10-plex and offline peptide fractionation. Finally, exciting perspectives for data-independent acquisition are highlighted with reproducible identification of 55 000 unique peptides covering 5900 proteins in half an hour of MS analysis.

An Optimized Shotgun Strategy for the Rapid Generation of Comprehensive Human Proteomes.

This study investigates the challenge of comprehensively cataloging the complete human proteome from a single-cell type using mass spectrometry (MS)-based shotgun proteomics. We modify a classical two-dimensional high-resolution reversed-phase peptide fractionation scheme and optimize a protocol that provides sufficient peak capacity to saturate the sequencing speed of modern MS instruments. This strategy enables the deepest proteome of a human single-cell type to date, with the HeLa proteome sequenced to a depth of ∼584,000 unique peptide sequences and ∼14,200 protein isoforms (∼12,200 protein-coding genes). This depth is comparable with next-generation RNA sequencing and enables the identification of post-translational modifications, including ∼7,000 N-acetylation sites and ∼10,000 phosphorylation sites, without the need for enrichment. We further demonstrate the general applicability and clinical potential of this proteomics strategy by comprehensively quantifying global proteome expression in several different human cancer cell lines and patient tissue samples.

Complete Mapping of Complex Disulfide Patterns with Closely-Spaced Cysteines by In-Source Reduction and Data-Dependent Mass Spectrometry.

Mapping of disulfide bonds is an essential part of protein characterization to ensure correct cysteine pairings. For this, mass spectrometry (MS) is the most widely used technique due to fast and accurate characterization. However, MS-based disulfide mapping is challenged when multiple disulfide bonds are present in complicated patterns. This includes the presence of disulfide bonds in nested patterns and closely spaced cysteines. Unambiguous mapping of such disulfide bonds typically requires advanced MS approaches. In this study, we exploited in-source reduction (ISR) of disulfide bonds during the electrospray ionization process to facilitate disulfide bond assignments. We successfully developed a LC-ISR-MS/MS methodology to use as an online and fully automated partial reduction procedure. Postcolumn partial reduction by ISR provided fast and easy identification of peptides involved in disulfide bonding from nonreduced proteolytic digests, due to the concurrent detection of disulfide-containing peptide species and their composing free peptides. Most importantly, intermediate partially reduced species containing only a single disulfide bond were also generated, from which unambiguous assignment of individual disulfide bonds could be done in species containing closely spaced disulfide bonds. The strength of this methodology was demonstrated by complete mapping of all four disulfide bonds in lysozyme and all 17 disulfide bonds in human serum albumin, including nested disulfide bonds and motifs of adjacent cysteine residues.

Analytic framework for peptidomics applied to large-scale neuropeptide identification.

Large-scale mass spectrometry-based peptidomics for drug discovery is relatively unexplored because of challenges in peptide degradation and identification following tissue extraction. Here we present a streamlined analytical pipeline for large-scale peptidomics. We developed an optimized sample preparation protocol to achieve fast, reproducible and effective extraction of endogenous peptides from sub-dissected organs such as the brain, while diminishing unspecific protease activity. Each peptidome sample was analysed by high-resolution tandem mass spectrometry and the resulting data set was integrated with publically available databases. We developed and applied an algorithm that reduces the peptide complexity for identification of biologically relevant peptides. The developed pipeline was applied to rat hypothalamus and identifies thousands of neuropeptides and their post-translational modifications, which is combined in a resource format for visualization, qualitative and quantitative analyses.

Ancient proteins resolve the evolutionary history of Darwin's South American ungulates.

No large group of recently extinct placental mammals remains as evolutionarily cryptic as the approximately 280 genera grouped as 'South American native ungulates'. To Charles Darwin, who first collected their remains, they included perhaps the 'strangest animal[s] ever discovered'. Today, much like 180 years ago, it is no clearer whether they had one origin or several, arose before or after the Cretaceous/Palaeogene transition 66.2 million years ago, or are more likely to belong with the elephants and sirenians of superorder Afrotheria than with the euungulates (cattle, horses, and allies) of superorder Laurasiatheria. Morphology-based analyses have proved unconvincing because convergences are pervasive among unrelated ungulate-like placentals. Approaches using ancient DNA have also been unsuccessful, probably because of rapid DNA degradation in semitropical and temperate deposits. Here we apply proteomic analysis to screen bone samples of the Late Quaternary South American native ungulate taxa Toxodon (Notoungulata) and Macrauchenia (Litopterna) for phylogenetically informative protein sequences. For each ungulate, we obtain approximately 90% direct sequence coverage of type I collagen α1- and α2-chains, representing approximately 900 of 1,140 amino-acid residues for each subunit. A phylogeny is estimated from an alignment of these fossil sequences with collagen (I) gene transcripts from available mammalian genomes or mass spectrometrically derived sequence data obtained for this study. The resulting consensus tree agrees well with recent higher-level mammalian phylogenies. Toxodon and Macrauchenia form a monophyletic group whose sister taxon is not Afrotheria or any of its constituent clades as recently claimed, but instead crown Perissodactyla (horses, tapirs, and rhinoceroses). These results are consistent with the origin of at least some South American native ungulates from 'condylarths', a paraphyletic assembly of archaic placentals. With ongoing improvements in instrumentation and analytical procedures, proteomics may produce a revolution in systematics such as that achieved by genomics, but with the possibility of reaching much further back in time.

Rapid and deep proteomes by faster sequencing on a benchtop quadrupole ultra-high-field Orbitrap mass spectrometer.

Shotgun proteomics is a powerful technology for global analysis of proteins and their post-translational modifications. Here, we investigate the faster sequencing speed of the latest Q Exactive HF mass spectrometer, which features an ultra-high-field Orbitrap mass analyzer. Proteome coverage is evaluated by four different acquisition methods and benchmarked across three generations of Q Exactive instruments (ProteomeXchange data set PXD001305). We find the ultra-high-field Orbitrap mass analyzer to be capable of attaining a sequencing speed above 20 Hz, and it routinely exceeds 10 peptide spectrum matches per second or up to 600 new peptides sequenced per gradient minute. We identify 4400 proteins from 1 µg of HeLa digest using a 1 h gradient, which is an approximately 30% improvement compared to that with previous instrumentation. In addition, we show that very deep proteome coverage can be achieved in less than 24 h of analysis time by offline high-pH reversed-phase peptide fractionation, from which we identify more than 140,000 unique peptide sequences. This is comparable to state-of-the-art multiday, multienzyme efforts. Finally, the acquisition methods are evaluated for single-shot phosphoproteomics, where we identify 7600 unique HeLa phosphopeptides in one gradient hour and find the quality of fragmentation spectra to be more important than quantity for accurate site assignment.

Species identification of archaeological skin objects from Danish bogs: comparison between mass spectrometry-based peptide sequencing and microscopy-based methods.

Denmark has an extraordinarily large and well-preserved collection of archaeological skin garments found in peat bogs, dated to approximately 920 BC - AD 775. These objects provide not only the possibility to study prehistoric skin costume and technologies, but also to investigate the animal species used for the production of skin garments. Until recently, species identification of archaeological skin was primarily performed by light and scanning electron microscopy or the analysis of ancient DNA. However, the efficacy of these methods can be limited due to the harsh, mostly acidic environment of peat bogs leading to morphological and molecular degradation within the samples. We compared species assignment results of twelve archaeological skin samples from Danish bogs using Mass Spectrometry (MS)-based peptide sequencing, against results obtained using light and scanning electron microscopy. While it was difficult to obtain reliable results using microscopy, MS enabled the identification of several species-diagnostic peptides, mostly from collagen and keratins, allowing confident species discrimination even among taxonomically close organisms, such as sheep and goat. Unlike previous MS-based methods, mostly relying on peptide fingerprinting, the shotgun sequencing approach we describe aims to identify the complete extracted ancient proteome, without preselected specific targets. As an example, we report the identification, in one of the samples, of two peptides uniquely assigned to bovine foetal haemoglobin, indicating the production of skin from a calf slaughtered within the first months of its life. We conclude that MS-based peptide sequencing is a reliable method for species identification of samples from bogs. The mass spectrometry proteomics data were deposited in the ProteomeXchange Consortium with the dataset identifier PXD001029.

Comprehensive identification of SUMO2/3 targets and their dynamics during mitosis.

During mitosis large alterations in cellular structures occur rapidly, which to a large extent is regulated by post-translational modification of proteins. Modification of proteins with the small ubiquitin-related protein SUMO2/3 regulates mitotic progression, but few mitotic targets have been identified so far. To deepen our understanding of SUMO2/3 during this window of the cell cycle, we undertook a comprehensive proteomic characterization of SUMO2/3 modified proteins in mitosis and upon mitotic exit. We developed an efficient tandem affinity purification strategy of SUMO2/3 modified proteins from mitotic cells. Combining this purification strategy with cell synchronization procedures and quantitative mass spectrometry allowed for the mapping of numerous novel targets and their dynamics as cells progressed out of mitosis. This identified RhoGDIα as a major SUMO2/3 modified protein, specifically during mitosis, mediated by the SUMO ligases PIAS2 and PIAS3. Our data provide a rich resource for further exploring the role of SUMO2/3 modifications in mitosis and cell cycle regulation.

Analytical utility of mass spectral binning in proteomic experiments by SPectral Immonium Ion Detection (SPIID).

Unambiguous identification of tandem mass spectra is a cornerstone in mass-spectrometry-based proteomics. As the study of post-translational modifications (PTMs) by means of shotgun proteomics progresses in depth and coverage, the ability to correctly identify PTM-bearing peptides is essential, increasing the demand for advanced data interpretation. Several PTMs are known to generate unique fragment ions during tandem mass spectrometry, the so-called diagnostic ions, which unequivocally identify a given mass spectrum as related to a specific PTM. Although such ions offer tremendous analytical advantages, algorithms to decipher MS/MS spectra for the presence of diagnostic ions in an unbiased manner are currently lacking. Here, we present a systematic spectral-pattern-based approach for the discovery of diagnostic ions and new fragmentation mechanisms in shotgun proteomics datasets. The developed software tool is designed to analyze large sets of high-resolution peptide fragmentation spectra independent of the fragmentation method, instrument type, or protease employed. To benchmark the software tool, we analyzed large higher-energy collisional activation dissociation datasets of samples containing phosphorylation, ubiquitylation, SUMOylation, formylation, and lysine acetylation. Using the developed software tool, we were able to identify known diagnostic ions by comparing histograms of modified and unmodified peptide spectra. Because the investigated tandem mass spectra data were acquired with high mass accuracy, unambiguous interpretation and determination of the chemical composition for the majority of detected fragment ions was feasible. Collectively we present a freely available software tool that allows for comprehensive and automatic analysis of analogous product ions in tandem mass spectra and systematic mapping of fragmentation mechanisms related to common amino acids.