On the risk of false positive identification using multiple ion monitoring in qualitative mass spectrometry: Large-scale intercomparisons with a comprehensive mass spectral library

Analysts involved in qualitative mass spectrometry have long debated the minimum data requirements for demonstrating that signals from an unknown sample are identical to those from a known compound. Often this process is carried out by comparing a few selected ions acquired by multiple ion monitoring (MIM), with due allowance for expected variability in response. In a few past experiments with electron-ionization mass spectrometry (EI-MS), the number of ions selected and the allowable variability in relative abundance were tested by comparing one spectrum against a library of mass spectra, where library spectra served to represent potential false positive signals in an analysis. We extended these experiments by carrying out large-scale intercomparisons between thousands of spectra and a library of one hundred thousand EI mass spectra. The results were analyzed to gain insights into the identification confidence associated with various numbers of selected ions. A new parameter was investigated for the first time, to take into account that a library spectrum with a different base peak than the search spectrum may still cause a false positive identification. The influence of peak correlation among the specific ions in all the library mass spectra was also studied. Our computations showed that (1) false positive identifications can result from similar compounds, or low-abundance peaks in unrelated compounds if the method calls for detection at very low levels; (2) a MIM method's identification confidence improves in a roughly continuous manner as more ions are monitored, about one order of magnitude for each additional ion selected; (3) full scan spectra still represent the best alternative, if instrument sensitivity is adequate. The use of large scale intercomparisons with a comprehensive library is the only way to provide direct evidence in support of these conclusions, which otherwise depend on the judgment and experience of individual analysts. There are implications for residue chemists who would rely on standardized confirmation criteria to assess the validity of a given confirmatory method. For example, standardized confirmation criteria should not be used in the absence of interference testing and rational selection of diagnostic ions.     

Library search of mass spectra with a new matching algorithm based on substructure similarity.

A new matching algorithm for library searches of mass spectra is presented in this paper. The algorithm is based on the substructure similarity of substances. It emphasizes m/z positions rather than abundance values. 32 spectra, whose corresponding molecular weights are less than 200, were randomly selected from a mass library of 61,993 spectra and taken as targets of library search to illustrate the availability of this algorithm. The results show that the algorithm is better than the one built in a commercial instrument when there is no spectrum of the unknown in the library but there are similar ones.     

Chemical substructure identification by mass spectral library searching

A library-search procedure that identifies structural features of an unknown compound from its electron-ionization mass spectrum is described. Like other methods, this procedure first retrieves library compounds whose spectra are most similar to the spectrum of an unknown compound. It then deduces structural features of the unknown compound from the chemical structures of the retrievals. Unlike other methods, the significance of each retrieved spectrum is weighted according to its similarity to the spectrum of the unknown compound. Also, a “peaks-in-common” screening step serves to reduce search times and an optimized dot product function provides the match factor. If the molecular weight of the unknown compound is provided, the identification of certain substructures can be improved by including “neutral loss” peaks. Correlations between the presence of a substructure in a test compound and its presence among library retrievals were derived from the results of searching the NIST/EPA/NIH reference library with a 7891 compound test set. These correlations allow the estimation of probabilities of substructure occurrence and absence in an unknown compound from the results of a library search. This method may be viewed as an optimization of the “K-nearest neighbor” method of Isenhour and co-workers, with improvements that arise from spectrum screening, peak scaling, an optimal distance measure, a relative-distance weighting scheme, and a larger reference library.     

Computer identification of infrared spectra by correlation-based file searching

A new method for the computerized search and identification of infrared spectra has been developed and evaluated. Based on cross-correlation, the search system utilizes all spectral information in a digitized spectrum when it attempts to match an unknown spectrum to one in a small library of known spectra. To evaluate a spectral match, the search program calculates the cross-correlation function between the unknown and known (library) spectra which indicates their degree of similarity and allows library spectra to be ranked in order of probability of match to the unknown spectrum. In this study, several small infrared spectral libraries of structurally similar compounds were searched under conditions which examined the sensitivity of the search method to chemical and instrumental variations. Because the correlation technique is slower than conventional file-searching methods, it will probably find greatest use in the search of small collections of similar spectra or as a match-ranking procedure following preliminary selection by a faster search method.     

The use of MS classifiers and structure generation to assist in the identification of unknowns in effect-directed analysis

Structure generation and mass spectral classifiers have been incorporated into a new method to gain further information from low-resolution GC-MS spectra and subsequently assist in the identification of toxic compounds isolated using effect-directed fractionation. The method has been developed for the case where little analytical information other than the mass spectrum is available, common, for example, in effect-directed analysis (EDA), where further interpretation of the mass spectra is necessary to gain additional information about unknown peaks in the chromatogram. Structure generation from a molecular formula alone rapidly leads to enormous numbers of structures; hence reduction of these numbers is necessary to focus identification or confirmation efforts. The mass spectral classifiers and structure generation procedure in the program MOLGEN-MS was enhanced by including additional classifier information available from the NIST05 database and incorporation of post-generation ‘filtering criteria’. The presented method can reduce the number of possible structures matching a spectrum by several orders of magnitude, creating much more manageable data sets and increasing the chance of identification. Examples are presented to show how the method can be used to provide ‘lines of evidence’ for the identity of an unknown compound. This method is an alternative to library search of mass spectra and is especially valuable for unknowns where no clear library match is available.     

New algorithm for the identification of mass spectra by the computer library search

A library search algorithm for the identification of mass spectra is described. The algorithm creates the mass vector of an unknown compound spectrum and sequentially compares it with the library files vector. A measure indicating similarity of compares vectors - similarity index is calculated on the basis of weighted factors of identical elements of both vectors. A diagnosticity of vectors element defined as a function of mass distribution of library file is taken as an important parameter in similarity index calculation.     

Interpretation Automatique des Spectres de Masse de Composes Organiques. Mise au Point

Computerized methods for interpretation of mass spectra are increasing and many papers have now been published. Three different approaches can be used to identify an unknown compound. These methods are reviewed and discussed. First, the heuristic technique which tries to simulate the reasoning of the chemist and deduce the formulae. The only information needed are the mass spectra, the empirical formulae and the n.m.r. spectra. Some promising results have been obtained but the method has important restrictions. Another approach represents the mass spectra as points in a hyperspace. By developing decision surfaces it is possible to classify an unknown compound. This is called pattern recognition and the different empirical methods for recognizing patterns in mass spectral data are explained and reported. The last and simplest technique is to match an unknown spectrum against a library of standard references. When the unknown spectrum is in the library, this approach gives the best results.     

Towards a full reference library of MSn spectra. II: A perspective from the library of pesticide spectra extracted from the literature/Internet

To gain perspective on building full transferable libraries of MSⁿ spectra from their diverse/numerous collections, a new library was built from 1723 MS^>1 spectra (mainly MS² spectra) of 490 pesticides and related compounds. Spectra acquired on different types of tandem instruments in various experimental conditions were extracted from 168 literature articles and Internet sites. Testing of the library was based on searches where 'unknown' and reference spectra originated from different sources (mainly from different laboratories) were cross‐compared. The NIST 05 MS² library was added to the reference spectra. The library searches were performed with all the test spectra or were divided into different subsamples containing (a) various numbers of replicate spectra of test compounds or (b) spectra acquired from different instrument types. Thus, the dependence of true/false search (identification) result rates on different factors was explored. The percentage of 1^st rank correct identifications (true positives) for the only 'unknown' mass spectrum and two and more reference spectra and matching precursor ion m/z values was 89%. For qualified matches, above the cut‐off match factor, that rate decreased to 80%. The corresponding rates based on the best match for two and more 'unknown' and reference spectral replicates were 89–94%. For quadrupole instruments, the rates were even higher: 91–95% (one 'unknown' spectrum) and 90–100% (two and more such spectra). This study shows that MS² spectral libraries generated from the numerous literature/Internet sources are not less efficient for the goal of identification of unknown compounds including pesticides than very common EI‐MS¹ libraries and are almost as efficient as the most productive from current MS² spectral databases. Such libraries may be used as individual reference databases or supplements to large experimental spectral collections covering many groups of abundant compounds and different types of tandem mass spectrometers. Copyright © 2011 John Wiley & Sons, Ltd.     

Computerunterstützte Spektreninterpretation zur Strukturaufklärung organischer Verbindungen

A computerized system to propose structures for an unknown compound is described. It uses a sophisticated library search technique. The philosophy for selecting and evaluating suitable spectral features is presented, using mass spectroscopy as an example.     

Combined use of ESI–QqTOF-MS and ESI–QqTOF-MS/MS with mass-spectral library search for qualitative analysis of drugs

The potential of the combined use of ESI–QqTOF-MS and ESI–QqTOF-MS/MS with mass-spectral library search for the identification of therapeutic and illicit drugs has been evaluated. Reserpine was used for standardizing experimental conditions and for characterization of the performance of the applied mass spectrometric system. Experiments revealed that because of the mass accuracy, the stability of calibration, and the reproducibility of fragmentation, the QqTOF mass spectrometer is an appropriate platform for establishment of a tandem-mass-spectral library. Three-hundred and nineteen substances were used as reference samples to build the spectral library. For each reference compound, product-ion spectra were acquired at ten different collision-energy values between 5 eV and 50 eV. For identification of unknown compounds, a library search algorithm was developed. The closeness of matching between a measured product-ion spectrum and a spectrum stored in the library was characterized by a value called “match probability”, which took into account the number of matched fragment ions, the number of fragment ions observed in the two spectra, and the sum of the intensity differences calculated for matching fragments. A large value for the match probability indicated a close match between the measured and the reference spectrum. A unique feature of the library search algorithm—an implemented spectral purification option—enables characterization of multi-contributor fragment-ion spectra. With the aid of this software feature, substances comprising only 1.0% of the total amount of binary mixtures were unequivocally assigned, in addition to the isobaric main contributors. The spectral library was successfully applied to the characterization of 39 forensic casework samples. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible to authorized users.     

A quantitative measure of the reliability of searches of spectral libraries

A quantitative measure of library search reliability has been developed. Applications of the quantitative reliability metric (QRM) for evaluating the reliability of library searches for unknown target spectra and the use of this measure to detect the failure of a library search caused by noise, contaminant peaks and missing library spectra are discussed. The effects of noise and composite infrared spectra of mixtures on the QRM are examined for test sets of 561 infrared spectra. The QRM is also used to evaluate the performance of a search of an infrared library compressed by eigenvector projection.     

Identification of unknown compounds using data bases and computer simulation of mass spectra

The possibility of identification based on the comparison of experimental electron-ionization mass spectrum of an unknown (in our case, model) compound with the mass spectra of the candidate compounds generated by the Mass Frontier software has been demonstrated by the example of three model compounds. The structural isomers of the identified substances found in the ChemExper database have been used as the candidate compounds. The candidate substances have been ranged by the degree of similarity between their simulated mass spectra and the experimental mass spectrum of the unknown compound. The mass spectra have been compared on the basis of the algorithm used in the NIST MS Search standard search system. In all three cases, the sought-after structure has been indicated as the most probable one of all the candidate structures.     

A computer search system for similar organic compounds in carbon-13 nuclear magnetic resonance data files

From the ¹³C-NMR spectrum of an unknown compound, the system provides a list of compounds ranked according to their similarity to the unknown. The similarity is estimated in a three-dimensional feature space, rather than by direct match of all peaks. All the spectra in the library are first converted to pattern points in the feature space by a dimensionality-reduction method. Thus, the search for similar compounds is simplified to a search for points within a given distance from the point representing the unknown. The compounds listed can be offered as the result or used for further operations (match of carbon number and peak position) in order to get a more exact result. An auto-optimization option is included to provide efficiency and user convenience.     

A correlation method in library search

The identification of unknown pure compounds or mixtures by means of mass spectral library search can be improved by partly resolving the spectra of the individual components within the spectrum of the measured unknown. This is accomplished by investigating sequential spectra in series of spectra; masses with highly correlating sequential intensities are clustered into individual groups. On the assumption that correlated masses belong to the same component spectrum, a filtering algorithm is developed to exclude spectra of non-identical compounds. The basic ideas, methods, examples and experiences gained with applications are reported.     

INFERCNMR: a 13C NMR interpretive library search system

INFERCNMR is an automated (13)C NMR spectrum interpretation aid for use either as a stand-alone program or as a component of a comprehensive, computer-based system for the characterization of chemical structure. The program is an interpretive library search which requires a database of assigned (13)C NMR spectra. An interpretive library search does not require overall structural similarity between an unknown and a library entry in order to retrieve a substructure common to both. Input consists of the chemical shift and one-bond proton-carbon multiplicity of each signal in the spectrum, and the molecular formula of the unknown. Program output is one or more substructures predicted to be present in the unknown, each of which is assigned an estimated prediction accuracy.     

Cluster chemical ionization for improved confidence level in sample identification by gas chromatography/mass spectrometry

Upon the supersonic expansion of helium mixed with vapor from an organic solvent (e.g. methanol), various clusters of the solvent with the sample molecules can be formed. As a result of 70 eV electron ionization of these clusters, cluster chemical ionization (cluster CI) mass spectra are obtained. These spectra are characterized by the combination of EI mass spectra of vibrationally cold molecules in the supersonic molecular beam (cold EI) with CI-like appearance of abundant protonated molecules, together with satellite peaks corresponding to protonated or non-protonated clusters of sample compounds with 1-3 solvent molecules. Like CI, cluster CI preferably occurs for polar compounds with high proton affinity. However, in contrast to conventional CI, for non-polar compounds or those with reduced proton affinity the cluster CI mass spectrum converges to that of cold EI. The appearance of a protonated molecule and its solvent cluster peaks, plus the lack of protonation and cluster satellites for prominent EI fragments, enable the unambiguous identification of the molecular ion. In turn, the insertion of the proper molecular ion into the NIST library search of the cold EI mass spectra eliminates those candidates with incorrect molecular mass and thus significantly increases the confidence level in sample identification. Furthermore, molecular mass identification is of prime importance for the analysis of unknown compounds that are absent in the library. Examples are given with emphasis on the cluster CI analysis of carbamate pesticides, high explosives and unknown samples, to demonstrate the usefulness of Supersonic GC/MS (GC/MS with supersonic molecular beam) in the analysis of these thermally labile compounds. Cluster CI is shown to be a practical ionization method, due to its ease-of-use and fast instrumental conversion between EI and cluster CI, which involves the opening of only one valve located at the make-up gas path. The ease-of-use of cluster CI is analogous to that of liquid CI in ion traps with internal ionization, and is in marked contrast to that of CI with most other standard GC/MS systems that require a change of the ion source.     

Identification of polymers by library search of pyrolysis mass spectra and pattern recognition analysis

A library of mass spectra of polymers containing about 200 entries is described. These spectra were obtained by direct pyrolysis-electron-impact mass spectrometry, i.e., by heating the polymers in the direct insertion probe for solid samples at a constant heating rate and recording repetitive mass spectra during the temperature rise. The library can be used both as a data base for library searches and as a training set for a pattern recognition analysis. The algorithm used to generate and search the files and a few applications of the library search and pattern recognition analysis are presented.     

Application of a text search system based on boolean strategy to mass spectral data identification

A general algorithm for text searching, operated on a tape-based minicomputer, has already been reported. This paper presents the application of the general text-searching algorithms to the Registry of Mass Spectral Data of 18,806 different entries. The text format allows multi-information input to be used to search the spectral library on the basis of data not necessarily extracted from mass spectra. Two library files have been generated; one is approximately half the size of the other, less important information having been deleted. The shorter library contains all 18,806 entries but enjoys much faster search times. Batch processing of searches is also possible. The text search is shown to be versatile in its operation, as the user can construct searches to be either broad or very selective, depending on the application. The search also has the capability to examine the data base internally and to check certain data for their validity.     

Towards a full reference library of MS(n) spectra. Testing of a library containing 3126 MS2 spectra of 1743 compounds

A library consisting of 3766 MS(n) spectra of 1743 compounds, including 3126 MS2 spectra acquired mainly using ion trap (IT) and triple-quadrupole (QqQ) instruments, was composed of numerous collections/sources. Ionization techniques were mainly electrospray ionization and also atmospheric pressure chemical ionization and chemical ionization. The library was tested for the performance in identification of unknowns, and in this context this work is believed to be the largest of all known tests of product-ion mass spectral libraries. The MS2 spectra of the same compounds from different collections were in turn divided into spectra of 'unknown' and reference compounds. For each particular compound, library searches were performed resulting in selection by taking into account the best matches for each spectral collection/source. Within each collection/source, replicate MS2 spectra differed in the collision energy used. Overall, there were up to 950 search results giving the best match factors and their ranks in corresponding hit lists. In general, the correct answers were obtained as the 1st rank in up to 60% of the search results when retrieved with (on average) 2.2 'unknown' and 6.2 reference replicates per compound. With two or more replicates of both 'unknown' and reference spectra (the average numbers of replicates were 4.0 and 7.8, respectively), the fraction of correct answers in the 1st rank increased to 77%. This value is close to the performance of established electron ionization mass spectra libraries (up to 79%) found by other workers. The hypothesis that MS2 spectra better match reference spectra acquired using the same type of tandem mass spectrometer (IT or QqQ) was neither strongly proved nor rejected here. The present work shows that MS2 spectral libraries containing sufficiently numerous different entries for each compound are sufficiently efficient for identification of unknowns and suitable for use with different tandem mass spectrometers.     

Comparison of different search engines using validated MS/MS test datasets

Massive amounts of tandem mass spectra are produced in high-throughput proteomics studies. The manual interpretation of these spectra is not feasible. Instead, search engines are used to match the tandem mass spectra with sequence information contained in proteomics and genomics databases. Typically, these search engines provide a list of the best matching peptide sequences for an individual tandem mass spectrum. As well, they provide scores that are somewhat related to the confidence level in the match. Many peptide tandem mass spectra search engines have been reported. These search engines provide very different results depending on the type of mass spectrometers used and their input parameters. Here we describe a comparative analysis of different search engines using validated test sets of tandem mass spectra. We have defined test sets of MS/MS spectra derived from high throughput proteomics experiments performed by HPLC-ESI-MS/MS on ion trap (LCQ) and tandem quadrupole time-of-flight instruments with a pulsar functionality (Qstar Pulsar) mass spectrometers. We analyzed the ability of the different search engines to identify the correct peptides, and the cross-validations of the different search engines.