Development of algorithms for automated elucidation of spectral feature/substructure relationships in tandem mass spectrometry

A pattern-recognition/artificial-intelligence program, referred to as MAPS (method for analyzing patterns in spectra), is described for the identification of relationships that exist between the presence of substructures in molecules and the characteristic features they produce in mass spectrometry (MS) and MS/MS data. The MAPS algorithm discovers these relationships by intelligent analysis of a data base of MS and MS/MS spectra. The relationships found are expressed as rules, which may then be used to identify characterized substructures in “unknowns”. No prior knowledge of fragmentation pathways or rearrangements is assumed in the rule-generation process. While MAPS currently uses MS and MS/MS data, the approach (and much of the software) is equally suited to multiple-stage mass spectrometric data.     

Evaluation of automatically generated substructure identification rules from tandem mass spectra

Substructure identification rules for phenothiazine and barbiturate substructures were generated by using a new version of the Method for Analyzing Patterns in Spectra (MAPS) software. This software uses tandem mass spectra and known substructure content of reference compounds to provide “feature-combination“ rules. A feature-combination is a series of tandem mass spectral features which are completely unique to compounds containing a specified substructure. The current reference databases contain over 11,000 daughter spectra of 100 compounds acquired at two different collision gas pressures (i.e., single- and multiple-collision conditions). The results of rule evaluation procedures are presented and include a comparison of the spectral features developed in rule generation to those identified in documented fragmentation pathways of the indicated substructure. Two potential sources of error due to spectral feature and substructure “cross-correlation“ were identified. If errors occur, they can be detected by calculating cross-correlation coefficients and edited from the rules. A beneficial cross-correlation involving feature-combinations was also discovered. The rules obtained by using single- and multiple-collision data were further evaluated by applying them to tandem mass spectra of 20 test compounds (compounds not in the reference database). The results of these evaluations give a good indication of the utility of the rules for use in an automated structure elucidation system for tandem mass spectrometry data.     

Generation of substructure identification rules using feature-combinations from tandem mass spectra

Software to interpret tandem mass spectra, entitled Method for Analyzing Patterns in Spectra (MAPS), has been developed to provide substructure information for an automated compound identification system, This software consists of several program modules which manipulate databases of tandem mass spectra and substructure information, generate substructure identification rules, and apply these rules to the tandem mass spectra of unknown compounds to identify components of their structure. The MAPS rule generation program has been modified to generate rules based on specific combinations of spectral features that occur concertedly. False positives are drastically reduced by searching for “feature-combinations” that have 100% uniqueness with respect to a reference database of compounds. Recall is increased by the determination of multiple feature-combinations indicative of the presence of a given substructure. Strategies were developed in the algorithm for the discovery of feature-combinations that avoid the computation “explosion” that occurs when working with a large number of spectral features. The rules developed have the form: “IF feature-eombination a (FC a) or FC b,..., or FC x, THEN substructure SSn is present.”     

Computer-assisted prediction of pesticide substructure using mass spectra

Mass spectral classifiers of 16 substructures that are present in basic structures of pesticides have been investigated to assist pesticide residues analysis as well as screening of pesticide lead compounds. Mass spectral data are first transformed into 396 features, and then Genetic Algorithm-Partial Least Squares (GA-PLS) as a feature selection method and Support Vector Machine (SVM) as a validation method are implemented together to get an optimization feature set for each substructure. At last, a statistical method which is AdaBoost algorithm combined with Classification and Regression Tree (AdaBoost-CART) is trained to predict the 16 substructures presence/absence using the optimization mass spectral feature set. It is demonstrated that the optimum feature sets can be used to predict the 16 pesticide substructures presence/absence with mostly 85-100% in recognition success rate instead of the original 396 features.     

Structural Feature Ions for Distinguishing N- and O-Linked Glycan Isomers by LC-ESI-IT MS/MS

Glycomics is the comprehensive study of glycan expression in an organism, cell, or tissue that relies on effective analytical technologies to understand glycan structure–function relationships. Owing to the macro- and micro-heterogeneity of oligosaccharides, detailed structure characterization has required an orthogonal approach, such as a combination of specific exoglycosidase digestions, LC-MS/MS, and the development of bioinformatic resources to comprehensively profile a complex biological sample. Liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS/MS) has emerged as a key tool in the structural analysis of oligosaccharides because of its high sensitivity, resolution, and robustness. Here, we present a strategy that uses LC-ESI-MS/MS to characterize over 200 N- and O-glycans from human saliva glycoproteins, complemented by sequential exoglycosidase treatment, to further verify the annotated glycan structures. Fragment-specific substructure diagnostic ions were collated from an extensive screen of the literature available on the detailed structural characterization of oligosaccharides and, together with other specific glycan structure feature ions derived from cross-ring and glycosidic-linkage fragmentation, were used to characterize the glycans and differentiate isomers. The availability of such annotated mass spectrometric fragmentation spectral libraries of glycan structures, together with such substructure diagnostic ions, will be key inputs for the future development of the automated elucidation of oligosaccharide structures from MS/MS data.

Practical aspects of liquid chromatography/electrospray tandem mass spectrometry for rapid identification of metabolites of a new antifungal agent SYN-2836 in dog urine

This report presents the structural elucidation of 12 urinary metabolites of SYN-2836, a new antifungal agent showing extensive metabolism in beagle dogs, using complementary liquid chromatography/tandem mass spectrometry (LC/MS/MS) methodologies. The 12 SYN-2836 metabolites were readily divided into four groups by considering that all three members of each group, although differing in masses, exhibited highly similar product ion mass spectra. This suggests that the metabolites within each group share a common major substructure. Therefore, all the grouped SYN-2836 metabolites were strategically identified by characterization of the major substructures followed by determination of the additional small substructures. This grouping strategy greatly facilitated the structural elucidation of these metabolites. Other strategies were also employed to achieve as rapid and unambiguous characterization of the SYN-2836 metabolites as possible.     

Structural characterization of sulfadiazine metabolites using H/D exchange combined with various MS/MS experiments

Two major metabolites and one minor metabolite of sulfadiazine were found in pig manure, using a special combination of different MS techniques like parent and product ion scans, H/D exchange, accurate mass measurement, and MS/MS experiments with substructures. N4-acetylsulfadiazine and 4-hydroxysulfadiazine were identified as major metabolites. N4-acetylsulfadiazine could be verified by H/D exchange and comparison with product ion spectra of a synthetic reference compound. In the case of 4-hydroxysulfadiazine, the majority of possible isomers could be discounted after H/D exchange. Substructure-specific MS/MS experiments with fragment ions and comparison with product ion spectra of two references revealed the presence of 4-hydroxysulfadiazine. The minor metabolite was characterized to some degree using H/D exchange and tandem mass spectrometry in combination with a high-resolution time of flight mass spectrometer. The aminopyrimidine moiety contained an additional modification with a likely elemental composition of C2H4O and no further acidic hydrogen.     

Automated assignment of high‐resolution collisionally activated dissociation mass spectra using a systematic bond disconnection approach

An essential component of the process of characterising chemical unknowns via mass spectrometry is the analysis of collisionally activated dissociation (CAD) mass spectra. Existing tools for the automated assignment of CAD spectra typically use a rule‐based approach which identifies those bonds that are likely to break. While valuable, the failure of explicitly rule‐based approaches to suggest rationalisations for a significant proportion of observed product ions led us to develop an alternative approach (elucidation of product ion connectivity, EPIC) based on high‐resolution mass spectrometry, systematic bond disconnection of the precursor structure, and ranking of the resulting substructures. We exemplify this approach with a reanalysis of published MS/MS data for two compounds taken from the literature. Copyright © 2005 John Wiley & Sons, Ltd.     

Challenges in the identification process of phenidate analogues in LC‐ESI‐MS/MS analysis: Information enhancement by derivatization with isobutyl chloroformate

A new analytical technique for the structural elucidation of four representative phenidate analogues possessing a secondary amine residue, which leads to a major/single amine‐representative fragment/product ion at m/z 84 both in their GC‐EI‐MS and LC‐ESI‐MS/MS spectra, making their identification ambiguous, was developed. The method is based on “in vial” chemical derivatization with isobutyl chloroformate in both aqueous and organic solutions, followed by liquid chromatography‐electrospray ionization mass spectrometry (LC‐ESI‐MS/MS). The resulting carbamate derivatives promote rich fragmentation patterns with full coverage of all substructures of the molecule, enabling detailed structural elucidation and unambiguous identification of the original compounds at low ng/mL levels.     

LC/MS and LC/MS/MS determination of protein tryptic digests

Tryptic digests were analyzed by means of online microbore liquid chromatography combined with mass spectrometry (LC/MS) for some common proteins. Following conventional enzymatic digestion with trypsin, the freeze-dried residues were dissolved in high-performance liquid chromatography (HPLC) eluent and subjected to gradient reversed-phase microbore HPLC separation with mass spectrometric detection. The latter was done in the full-scan single or tandem (MS/MS) mass spectrometry mode. The formation of gas-phase ions from dissolved analytes was accomplished at atmospheric pressure by pneumatically assisted electrospray (ion spray) ionization. This produced field-assisted ion evaporation of dissolved ions, which could then be mass-analyzed for molecular mass or structure. In the full-scan LC/MS mode, the masses for the peptide fragments in the tryptic digests can be determined as either their singly or multiply charged ions. When the molecular weights of the peptides lie outside the mass range of the mass spectrometer, the multiply charged feature of these experimental conditions still provides reliable molecular weight determinations. In addition, collision-activated dissociation (CAD) on selected peptide precursor ions provides online LC/MS/MS sequence information for the tryptic fragments. Results are shown for the tryptic digests of horse heart cytochrome c, bovine β-lactoglobulin A, and bovine β-lactoglobulin B.     

Block length determination of the block copolymer mPEG‐b‐PS using MALDI‐TOF MS/MS

The molar mass determination of block copolymers, in particular amphiphilic block copolymers, has been challenging with chromatographic techniques. Therefore, methoxy poly(ethylene glycol)‐b‐poly(styrene) (mPEG‐b‐PS) was synthesized by atom transfer radical polymerization (ATRP) and characterized in detail not only by conventional chromatographic techniques, such as size exclusion chromatography (SEC), but also by matrix‐assisted laser/desorption ionization tandem mass spectrometry (MALDI‐TOF MS/MS). As expected, different molar mass values were obtained in the SEC measurements depending on the calibration standards (either PEG or PS). In contrast, MALDI‐TOF MS/MS analysis allowed the molar mass determination of each block, by the scission of the weakest point between the PEG and PS block. Thus, fragments of the individual blocks could be obtained. The PEG block showed a depolymerization reaction, while for the PS block fragments were obtained in the monomeric, dimeric, and trimeric regions as a result of multiple chain scissions. The block length of PEG and PS could be calculated from the fragments recorded in the MALDI‐TOF MS/MS spectrum. Furthermore, the assignment of the substructures of the individual blocks acquired by MALDI‐TOF MS/MS was accomplished with the help of the fragments that were obtained from the corresponding homopolymers. © 2010 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2010     

Determination of estrogens and progestogens by mass spectrometric techniques (GC/MS, LC/MS and LC/MS/MS)

Steroid sex hormones and related synthetic compounds have been shown to provoke alarming estrogenic effects in aquatic organisms, such as feminization, at very low concentrations (ng/L or pg/L). In this work, different chromatographic techniques, namely, gas chromatography/mass spectrometry (GC/MS), liquid chromatography/mass spectrometry (LC/MS) and liquid chromatography/tandem mass spectrometry (LC/MS/MS), are discussed for the analysis of estrogens, both free and conjugated, and progestogens, and the sensitivities achieved with the various techniques are inter-compared. GC/MS analyses are usually carried out after derivatization of the analytes with bis(trimethylsilyl)trifluoroacetamide (BSTFA). For LC/MS and LC/MS/MS analyses, different instruments, ionization techniques (electrospray (ESI) and atmospheric pressure chemical ionization (APCI)), ionization modes (negative ion (NI) and positive ion (PI)) and monitoring modes (selected ion monitoring (SIM) and selected reaction monitoring (SRM)) are generally employed. Based on sensitivity and selectivity, LC/ESI-MS/MS is generally the method of choice for determination of estrogens in the NI mode and of progestogens in the PI mode (instrumental detection limits (IDLs) 0.1-10 ng/mL). IDLs achieved by LC/ESI-MS in the SIM mode and by LC/ESI-MS/MS in the SRM mode were, in general, comparable, although the selectivity of the latter is significantly higher and essential to avoid false positive determinations in the analysis of real samples. Conclusions and future perspectives are outlined.     

Recently developed GC/MS and LC/MS methods for determining NSAIDs in water samples

Pharmaceuticals have become major targets in environmental chemistry due to their presence in aquatic environments (following incomplete removal in wastewater treatment or point-source contaminations), threat to drinking water sources and concern about their possible effects to wildlife and humans. Recently several methods have been developed for the determination of drugs and their metabolites in the lower nanogram per litre range, most of them using solid-phase extraction (SPE) or solid-phase microextraction (SPME), derivatisation and finally gas chromatography mass spectrometry (GC-MS), gas chromatography tandem mass spectrometry (GC-MS/MS) and liquid chromatography electrospray tandem mass spectrometry (LC-ES/MS/MS). Due to the elevated polarity of non-steroidal anti-inflamatory drugs (NSAIDs), analytical techniques based on either liquid chromatography coupled to mass spectrometry (LC-MS) and gas chromatography coupled to mass spectrometry (GC-MS) after a previous derivatisation step are essential. The most advanced aspects of current GC-MS, GC-MS/MS and LC-MS/MS methodologies for NSAID analysis are presented.     

Discrimination of Thermoplastic Polyesters by MALDI-TOF MS and Py-GC/MS

The aim of this work is to discriminate thermoplastic polyester-polyethylene terephthalate (PET), polybutylene terephthalate (PBT), and polytrimethylene terephthalate (PTT), which cannot be easily identified by many methods. Both matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) and pyrolysis gas chromatography/mass spectrometry (Py-GC/MS) were applied to identify these polyesters owing to their analytical ability to determining polymers' chemical structure. The three thermoplastic polyesters can be easily distinguished by MALDI-TOF MS according to their different repeated units. Py-GC/MS was used to analyze their specific pyrolyzates. The three polyesters can be identified through their characteristic pyrolysis products as well.     

Rule extraction from a mutagenicity data set using adaptively grown phylogenetic-like trees

A public bacterial mutagenicity database was classified into 2-D structural families using a set of specific algorithms and clustering techniques that find overlapping classes of compounds based upon chemical substructures. Structure-activity relationships were learned from the biological activity of the compounds within each class and used to identify rules that define substructures potentially responsible for mutagenic activity. In addition, this method of analysis was used to compare the pharmacologically relevant substructure of test compounds with their potential toxic substructures making this a potentially valuable in silico profiling tool for lead selection and optimization.     

Identification of RNA sequence isomer by isotope labeling and LC–MS/MS

Recently, we developed a method for modified ribonucleic acid (RNA) analysis based on the comparative analysis of RNA digests (CARD). Within this CARD approach, sequence or modification differences between two samples are identified through differential isotopic labeling of two samples. Components present in both samples will each be labeled, yielding doublets in the CARD mass spectrum. Components unique to only one sample should be detected as singlets. A limitation of the prior singlet identification strategy occurs when the two samples contain components of unique sequence but identical base composition. At the first stage of mass spectrometry, these sequence isomers cannot be differentiated and would appear as doublets rather than singlets. However, underlying sequence differences should be detectable by collision‐induced dissociation tandem mass spectrometry (CID MS/MS), as y‐type product ions will retain the original enzymatically incorporated isotope label. Here, we determine appropriate instrumental conditions that enable CID MS/MS of isotopically labeled ribonuclease T1 (RNase T1) digestion products such that the original isotope label is maintained in the product ion mass spectrum. Next, we demonstrate how y‐type product ions can be used to differentiate singlets and doublets from isomer sequences. We were then able to extend the utility of this approach by using CID MS/MS for the confirmation of an expected RNase T1 digestion product within the CARD analysis of an Escherichia coli mutant strain even in the presence of interfering and overlapping digestion products from other transfer RNAs. Copyright © 2014 John Wiley & Sons, Ltd.     

Non-Target Screening of Veterinary Drugs Using Tandem Mass Spectrometry on SmartMass

Non-target screening of veterinary drugs using tandem mass spectrometric data was performed on the SmartMass platform. This newly developed software uses the characteristic fragmentation patterns (CFP) to identify chemicals, especially those containing particular substructures. A mixture of 17 sulfonamides was separated by ultra performance liquid chromatography (UPLC), and SmartMass was used to process the tandem mass spectrometry (MS/MS) data acquired on an Orbitrap mass spectrometer. The data were automatically extracted, and each sulfonamide was recognized and analyzed with a prebuilt analysis rule. By using this software, over 98 % of the false candidate structures were eliminated, and all the correct structures were found within the top 10 of the ranking lists. Furthermore, SmartMass could also be used to identify slightly modified contraband drugs and metabolites with simple prebuilt rules.      

Detection of oxygen addition peaks for terpendole E and related indole–diterpene alkaloids in a positive‐mode ESI‐MS

This report describes that a regular positive electrospray ionization mass spectrometry (MS) analysis of terpendoles often causes unexpected oxygen additions to form [M + H + O]⁺ and [M + H + 2O]⁺, which might be a troublesome in the characterization of new natural analogues. The intensities of [M + H + O]⁺ and [M + H + 2O]⁺ among terpendoles were unpredictable and fluctuated largely. Simple electrochemical oxidation in electrospray ionization was insufficient to explain the phenomenon. So we studied factors to form [M + H + O]⁺ and [M + H + 2O]⁺ using terpendole E and natural terpendoles together with some model indole alkaloids. Similar oxygen addition was observed for 1,2,3,4‐tetrahydrocyclopent[b]indole, which is corresponding to the substructure of terpendole E. In tandem MS experiments, a major fragment ion at m/z 130 from protonated terpendole E was assigned to the substructure containing indole. When the [M + H + O]⁺ was selected as a precursor ion, the ion shifted to m/z 146. The same 16 Da shift of fragments was also observed for 1,2,3,4‐tetrahydrocyclopent[b]indole, indicating that the oxygen addition of terpendole E took place at the indole portion. However, the oxygen addition was absent for some terpendoles, even whose structure resembles terpendole E. The breakdown curves characterized the tandem MS features of terpendoles. Preferential dissociation into m/z 130 suggested the protonation tendency at the indole site. Terpendoles that are preferentially protonated at indole tend to form oxygen addition peaks, suggesting that the protonation feature contributes to the oxygen additions in some degrees. © 2014 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons, Ltd.     

Approaches towards the automated interpretation and prediction of electrospray tandem mass spectra of non-peptidic combinatorial compounds

Combinatorial chemistry is widely used within the pharmaceutical industry as a means of rapid identification of potential drugs. With the growth of combinatorial libraries, mass spectrometry (MS) became the key analytical technique because of its speed of analysis, sensitivity, accuracy and ability to be coupled with other analytical techniques. In the majority of cases, electrospray mass spectrometry (ES-MS) has become the default ionisation technique. However, due to the absence of fragment ions in the resulting spectra, tandem mass spectrometry (MS/MS) is required to provide structural information for the identification of an unknown analyte. This work discusses the first steps of an investigation into the fragmentation pathways taking place in electrospray tandem mass spectrometry. The ultimate goal for this project is to set general fragmentation rules for non-peptidic, pharmaceutical, combinatorial compounds. As an aid, an artificial intelligence (AI) software package is used to facilitate interpretation of the spectra. This initial study has focused on determining the fragmentation rules for some classes of compound types that fit the remit as outlined above. Based on studies carried out on several combinatorial libraries of these compounds, it was established that different classes of drug molecules follow unique fragmentation pathways. In addition to these general observations, the specific ionisation processes and the fragmentation pathways involved in the electrospray mass spectra of these systems were explored. The ultimate goal will be to incorporate our findings into the computer program and allow identification of an unknown, non-peptidic compound following insertion of its ES-MS/MS spectrum into the AI package. The work herein demonstrates the potential benefit of such an approach in addressing the issue of high-throughput, automated MS/MS data interpretation.