Peak lists

Multivariate data analysis usually starts with generating a set of spectra and the corresponding chemical structures as a result of a spectrum similarity search in a spectrum database. The peak data are transformed into a set of spectral features and the chemical structures are encoded into molecular descriptors [80]. A spectral feature is a property that can be automatically computed from a mass spectrum. Typical spectral features are the peak intensity at a particular mass/charge value, or logarithmic intensity ratios. The goal of transformation of peak data into spectral features is to obtain descriptors of spectral properties that are more suitable than the original peak list data. 

Figure 6 Steps in automated assignment. (1) Select the lowest energy structures from iteration / — 1 that are used to interpret the spectra. (2) For each peak, list all possible assignments compatible with the resonances within a frequency mnge. (3) Extract a distance for each assignment possibility from the ensemble of structures. (4) Use the distances to assign ambiguous NOEs. (5) Calibrate the peak volumes to obtain distance restraints. (6) Calculate structures based on the new restraints.

Example 1, Poly(vinyl alcohol). The first example is given for the carbon-13 spectrum of Poly(vinyl alcohol). Figure 2 shows a plot of the carbon spectrum and a peak listing with assignments from the user s database. The assignments constitute a difficult part of the analysis... 

Figure 5. The C-15 (125.76 Hz) spectrum of approximately 20% w/v copolymer vinylidene chloride Isobutylene In CDCI at 24°C and a peak listing from the Polymer Analysis program.

Note The peaks listed are singlets, unless described as doublets (d), triplets (t), quartets (q), or multiplets (m). Coupling constants (in Hz) are given in parentheses. 

Then the mass spectrum of the mentioned peptide mixture is measured. The set of molecular mass values (peak list) corresponding to individual peptides is characteristic for the protein and can be considered as its fingerprint. 

The obtained peak list together with other data (biological species, possible posttransla-tional modifications of amino acids, etc.) is then submitted to a software tool (usually publicly available) and searched against a certain protein database, which leads to protein identification. The majority of available software tools also offer information on the statistical probability of protein identification. 

Requirement 2. Self-consistency The peak lists must be faithful representations of the NOESY spectra, and the chemical shift positions of the NOESY cross peaks must be correctly calibrated to fit the chemical shift lists within the chemical shift tolerances. The range of allowed chemical shift variations ( tolerances ) for 1H should not exceed 0.02 ppm when working with homonuclear [1H,1H]-NOESY spectra, or 0.03 ppm when work-... 

In principle, a de novo protein structure determination requires one round of 7 Candid cycles. This is realistic for projects where an essentially complete chemical shift list is available and much effort was made to prepare a complete high-quality input of NOESY peak lists. In practice, it turned out to be more efficient to start a first round of Candid analysis without excessive work for the preparation of the input peak list, using an slightly incomplete list of safely identifiable NOESY cross peaks, and then to use the result of the first round of Candid assignment and structure determination as additional information from which to prepare an improved, more complete NOESY peak list as input for a second round of 7 Candid cycles. 

Comparison of the peaks listed in Table I with the spectra of Figure 8 verifies the assertion made above that the most Intense lines in the 6 hr spectrum are from the reactants. The sub-spectrum of smaller lines are the new features, and so it seems that even after 6 hrs, some reactant still remains. More reaction had probably occurred than is indicated by the spectra since some of the product was lost to the NMR in the Insoluble fraction. Concentrating on the sub-spectrum of 20 new peaks, at least five spectral features are evident that support the mechanism for the condensation reaction given above. 

Table 9-5 and Figure 9-20 show partial mass spectral data for representative carbonyl compounds. You can analyze each of the spectra to try to explain each of the peaks listed. 

Now select the Interpolation mode in the Peak Picking Options dialog box and repeat the procedure. Compare the results tor the different methods on the screen and in the corresponding peak lists. Expand the spectrum in the region of a peak and inspect the effect of the interpolation. 

Lets you define and inspect parameters which are required for export of peak lists to... 

Patterson Correlation Refinement. To select which of the orientations determined from the rotation search is the correct solution a Patterson correlation refinement of the peak list of the rotation function was performed. This was carried out by minimization against a target function defined by Brunger (1990) and as implemented in XPLOR. The search model, P2, was optimized for each of the selected peaks of the rotation function. 

The NOE matching protocol is described pictorially in Figure 5.1. Two files are needed for input an experimental NOE peak list with ligand protons assigned and a set of trial binding poses to be evaluated or scored. The list of experimental peaks is typically derived from a 3D 13C-edited, 13C/15N-filtered HSQC-NOESY spectrum.1116-201 (Hereafter, this type of spectrum will be referred to as a 3D X-filtered NOESY spectrum.)... 

If the peak list was saved as a text file, browse to the file location otherwise, paste the list directly into the Query field. 

The peptide tolerance is a window around each mass value in the peak list within which a theoretical database peptide mass must fall, in order to be matched. 

Almost all papers on pyrans and derivatives contain information such as peak listings for routine mass spectrometry however, there have only been a handful of papers that describe new types of mass spectrometry or fragmentation patterns that have not previously been described in CHEC(1984) and CHEC-II(1996). 

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