Structure predicting from mass spectra

More complex detective work is required to analyze large biomolecules and drugs. However, fragmentation generally follows predictable patterns, and one compound can be identified by comparing its mass spectrum with those of other known compounds with similar structures. In Fig. 2, we see the spectrum of a sample of blood from a newborn infant. The blood is being analyzed to determine whether the child has phenylketonuria. The presence of the compound phenylalanine is a positive indication of the condition. Some... 

The successful prediction of superconductivity in the high pressure Si phases added much credibility to the total energy approach generally. It can be argued that Si is the best understood superconductor since the existence of the phases, their structure and lattice parameters, electronic structure, phonon spectrum, electron-phonon couplings, and superconducting transition temperatures were all predicted from first principles with the atomic number and atomic mass as the main input parameters. 

When working with non-radiolabeled drugs the major challenge is to find metabolites in the biological matrices. Because the enzymes responsible for metabolism are quite well characterized metabolic changes can partially be predicted. For example hydroxylation of the parent drug is in many cases the principal metabolic pathway. From a mass spectrometric point of view it results in an increase of 16 units in the mass spectrum. In the full-scan mode an extracted ion current profile can be used to screen for potential metabolites. In a second step a product ion spectrum is recorded for structural interpretation. Ideally, one would like to obtain relative molecular mass information and the corresponding product ion spectrum in the same LC-MS run. This information can be obtained by data dependant acquisition (DDA), as illustrated in Fig. 1.39. 

The structures deduced from the mass spectra must account for the observed equivalent chain length (ECL) or Kovats indices (KI) (Carlson et al., 1998 Katritzky and Chen, 2000 Zarei and Atabati, 2005). The values for monomethylalkanes (Mold et al., 1966 Szafranek et al., 1982) can be used to estimate the expected ECL or KI for a di-, tri- or tetramethyl-alkane structure proposed from a mass spectrum. For example, a dimethylalkane, such as 3,11 -dimethylnonacosane, with 31 carbons, would have its elution time decreased by about 0.3 carbons for the 3-methyl group and about 0.7 carbons for the 11-methyl group. Thus, the predicted ECL is approximately 30 and this is the ECL observed. 

Q Given a structure, predict the major ions that will be observed in the mass spectrum from fragmentation of the molecular ion. Use these predictions to determine whether a proposed structure is consistent with the spectrum. 

Mass spectrometry is, however, a destructive technique—it consumes sample, albeit very small amounts. It is not a universal detector. There are entire classes of compounds that respond differentially in the mass spectrometer under varied conditions, poorly in general, or not at all. The inference of structure from mass spectra is also highly empirical. Regardless of effort, the theoretical prediction of the mass spectrum from a given structure has not been... 

This is accomplished by creating the parent ion from the structure candidate and storing it in an ion list. The production rnles are applied and lead to a series of ionic strnctnre fragments that are appended to the list. In the next step, fragmentation is predicted for each ion, and a hypothetical mass spectrum is created and added to a spectrnm list. The spectrnm list contains the ion and the mass and charge value and its relative abnndance. The relative abundance is required since the same ion may occnr mnltiple times as resnlt of fragmentation of different substructures. If all ions in the ion list are compnted, the spectrum list contains all data for the hypothetical mass spectrnm of the candidate structure. 

MSPRUNE is an extension to MSRANK that works with a list of candidate structures from CONGEN and the mass spectrum of the query molecule to predict typical fragmentations for each candidate structure. 

Cyclization to form 6-membered rings competes more favorably with hydride shift. Linear hexadienes with terminal CFl2-groups (expected products of equation 18) are recovered in a yield of 0.6 pmol/A-s for the case = 3, while cyclohexene constitutes a yield of 0.35 pmol/A-s 1-methylcyclopentene 0.08 pmol/A-s and the other methylcyclopentenes 0.06 pmol/A-s. Products characteristic of free CeHn cations that rearrange to the most stable allylic structures—2,4-hexadienes and branched CeHio dienes—are recovered in a yield of 0.15 pmol/A-s. As in the n = 2 case, the products from cations produced in ion-neutral complexes greatly exceed those from free cations produced by simple bond fission, just as the 70 eV mass spectrum would predict. 

For problems of practical interest, however, the relationship F can neither be formulated as a mathematical equation nor as an algorithm. Consequently, methods for the prediction of the mass spectrum from the chemical structure have had only very limited success. A similar difficult situation arises for the inverse problem, spectra interpretation. Figure 1. Only for selected cases can the relationship... 

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