MSSS Mass Spectral Search

Maximum benefit from Gas Chromatography and Mass Spectrometry will be obtained if the user is aware of the information contained in the book. That is, Part I should be read to gain a practical understanding of GC/MS technology. In Part II, the reader will discover the nature of the material contained in each chapter. GC conditions for separating specific compounds are found under the appropriate chapter headings. The compounds for each GC separation are listed in order of elution, but more important, conditions that are likely to separate similar compound types are shown. Part II also contains information on derivatization, as well as on mass spectral interpretation for derivatized and underivatized compounds. Part III, combined with information from a library search, provides a list of ion masses and neutral losses for interpreting unknown compounds. The appendices in Part IV contain a wealth of information of value to the practice of GC and MS. 

The spray paint can was inverted and a small amount of product was dispensed into a 20 mL glass headspace vial. The vial was immediately sealed and was incubated at 80°C for approximately 30 min. After this isothermal hold, a 0.5-mL portion of the headspace was injected into the GC/MS system. The GC-MS total ion chromatogram of the paint solvent mixture headspace is shown in Figure 15. Numerous solvent peaks were detected and identified via mass spectral library searching. The retention times, approximate percentages, and tentative identifications are shown in Table 8 for the solvent peaks. These peak identifications are considered tentative, as they are based solely on the library search. The mass spectral library search is often unable to differentiate with a high degree of confidence between positional isomers of branched aliphatic hydrocarbons or cycloaliphatic hydrocarbons. Therefore, the peak identifications in Table 8 may not be correct in all cases as to the exact isomer present (e.g., 1,2,3-cyclohexane versus 1,2,4-cyclohexane). However, the class of compound (cyclic versus branched versus linear aliphatic) and the total number of carbon atoms in the molecule should be correct for the majority of peaks. 

Abstract A relatively small number of mammalian pheromones has been identified, in contrast to a plethora of known insect pheromones, but two remarkable Asian elephant/insect pheromonal linkages have been elucidated, namely, (Z)-7-dodecen-1-yl acetate and frontalin. In addition, behavioral bioassays have demonstrated the presence of a chemical signal in the urine of female African elephants around the time of ovulation. Our search for possible ovulatory pheromones in the headspace over female African elephant urine has revealed for the first time the presence of a number of known insect pheromones. This search has been facilitated by the use of a powerful new analytical technique, automated solid phase dynamic extraction (SPDE)/GC-MS, as well as by novel macros for enhanced and rapid comparison of multiple mass spectral data files from Agilent ChemStation . This chapter will focus on our methodologies and results, as well as on a comparison of SPDE and the more established techniques of solid phase microextraction (SPME) and stir bar sorptive extraction (SBSE). 

Of course one may employ automated library searches ( library percent reports ) to check for compound identities, but algorithms for library matching are not infallible, and mass spectral libraries are not exhaustive, thus some compounds of interest will likely not be identified. Additional dilemmas are presented by mere reliance on retention times and library percent reports to ascertain the presence of common or unique peaks from among multiple mass spectral data files. As illustrated in Table 2.1, the TICs from the GC-MS of urine from four elephants evidence a peak at essentially the same retention time, but the library search results are inconclusive as to their common identity or lack thereof. As will be seen below, our novel macros can assist in making such decisions for a large number of peaks. 

GC-MS analysis has become standard practice in semiochemical research. There is, however, a real danger that information based exclusively on the results of computerized library searches without mass spectral and retention-time comparison with authentic synthetic material can be introduced into the literature. This could be problem especially in mammalian semiochemistry, because researchers often are faced with the problem of having to identify large numbers of compounds of which many may have very uninformative mass spectra. A critical reader of the original publication could still be aware of the unverified nature of some of the information, but this may not be pointed out in later references to the work. 

A thorough search of the reconstructed ion chromatogram (RIC) was made to determine the mass spectra of all detectable components. The spectra were compared with those of reference standards when available or with the spectra from the mass spectral library. Molecular weights of more abundant constituents are shown in Figure b, many additional minor components were also characterized. A complete list of compounds characterized in this sample by GC-MS is given in Table I. 

A typical total ion current chromatogram of the Tenax trapped canned black truffle (Tuber Melanosporum) juice volatiles is shown in Figure 2. The compounds identified by GC-MS are listed in Table I in the order of elution from the GC column with their characteristic mass spectral data. The identification of these compounds was based on comparison of the mass spectra obtained with those stored in the NIH/EPA library and also with those of authentic compounds. Moreover, an additional search of published standard mass spectra to confirm the identity of unknowns was undertaken (16). 

Figure 5.9. Spectral search at Spectral Database Systems (SDBS). The infrared (IR), nuclear magnetic resonance H-NMR and 13C-NMR), electron spin resonance (ESR), and mass (MS) spectra of organic compounds and common biochemical compounds can be viewed/retrieved from SDBS.

Mass spectral quality is an important consideration in performing a successful GC-MS analysis. The quality of the mass spectra depends on (1) the concentration of the constituents in the sample solution, (2) the GC operating conditions used to resolve the peaks, and (3) excessive pressure fluctuation in the MS unit of the GC-MS system leading to distortion of the mass spectrum, especially an El mass spectrum, as reflected in the relative abundance of the ion peaks. The implication of (3) is that distortions of this type could lead to misinterpretation of the spectrum even though a library search is performed. 

The peak identification for the chromatogram shown in Figure 6.1.25 was done using MS spectral library searches. This identification is not always possible, since most compounds with a higher MW are not found in the commercial mass spectral libraries (such as NIST 2002, Wiley 7. etc.). The similarity between the spectra in each series of compounds can be used for peak identification, even when the compound is not found in the mass spectral library. This is exemplified in Figure 6.1.26, which shows the spectra of the B series of compounds shown in Table 6.1.10. 

The results for a Py-GC/MS analysis of a sample of poly(vinyl toluene) (mixed isomers) CAS 9017-21-4, Mw = 80,000 are shown in Figure 6.2.17. The pyrolysis was done from 0.4 mg material at 600° C in He at a heating rate of 20° C/ms with 10 s THT. The separation was done on a Carbowax column similar to other examples previously discussed (see Table 4.2.2). The peak identification for the chromatogram shown in Figure 6.2.17 was done using MS spectrai library searches only and is given in Table 6.2.11. Some of the isomer positions are tentative only and reported in Table 6.2.11 as they resulted with the highest probabiiity indicated by the mass spectral library search. 

The current mass spectral libraries (NIST 2002, Wiley 7) do not contain the spectra of these compounds, and therefore they were not identifiable by the MS library searches. The use of mass spectrum fragments can be of help in these situations. One example is the tentative identification for the peak with retention time of 75.48 min. (from Figure 6.9.2) as 4-methyl-1 - 1 -methyl-1 -[2-methyl-5-(methylethyl)cyclohexyl]ethyl benzene. The fragment assignments for the ions seen in the mass spectrum are shown in Figure 6.9.3. 

For identification purposes, two basic approaches have been used. In the first, a purified protein is enzymatically digested, the product peptide mixture is analyzed and a mass spectral pattern is obtained. This pattern, called the MS fingerprint , is used to search in internet-available protein or DNA databases.17 Information about protein origin and an estimate of its MW are required in order to improve the chances of a correct match. The search algorithm then theoretically digests all appropriate proteins in the database with the specified enzyme, and matches the... 

Identification or structural elucidation of an unknown compound is one of the most challenging tasks that can be undertaken by an analytical chemist. Where the analyst has milligram or more amounts of the unknown, MS is often used in conjunction with other techniques such as nuclear magnetic resonance (NMR) and IR spectroscopy. However, when there are only limited quantities of sample, the sensitivity of MS makes this the technique of choice for assembling structural information and, where no definitive conclusion can be reached on the mass spectral data alone, serves to limit the search to a particular class of chemicals or set of isomers. 

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