Deconvolution spectrum, proteins

In order to assess the size of the carbohydrate component, deglycosylated CHO IL-4 by A-glycanase was analyzed by ESI-MS. The deconvoluted spectrum displayed an MW of 14,955 Da, which conformed well to the theoretical MW of the protein (MW 14,963 Da) when considering the presence of three disulfide bonds in the protein. 

Figure 5.5 RPLC-MS of pi fractions. A-G represent pi ranges of 9.2-8.1, 8.1-7.0, 7.0 5.9, 5.9-4.8, 4.8-3.7, 3.7-2.6 and 2.6-1.5, respectively. Left panel, extracted mass chromatogram of each protein in the fraction middle panel, raw spectrum of each protein averaged over the top 80% of the LC peak right panel, deconvoluted spectrum (singly charged) by MaxEntl. Only the total ion chromatogram is shown for fraction F no deconvoluted spectrum is shown for fraction G. Reprinted with permission from F. Zhou and M. Johnston, Analytical Chemistry 76, 2734—2740, Copyright 2004 American Chemical Society...

The raw and deconvoluted mass spectra from scans 2000-2025 of the eighth protein fraction are shown in Figure 5.9a and b, as an example of proteins that are not isotopicafly resolved. The most intense feature of the deconvoluted spectrum in Figure 5.9b, 16293 Da,... 

Fig. 3 LCMS Analysis of Fusion rCRALBP (A) RP-HPLC ultraviolet profile ( 220nm) froHi analysis of 1.5 (ig fusion human rCRALBP on a 50- X Vydac C18 column (lx 250 mm) at 50 lL/min usmg the indicated gradient. Solvent A was 0 1% trifluoracetic acid (TFA) and solvent B was 84% acetonitrile, containing about 0.07% TFA. (B) Reconstructed total ion current from electrospray-mass spectral analysis of the fusion rCRALBP liquid chromatography shown in A. (C) Electrospray-mass spectrum of fusion human rCRALBP indicating the presence of a protein of = 39,114 4 (calculated = 39,110). The deconvoluted spectrum is shown in the inset.

Fig 4 LCMS Analysis of Non-Fusion rCRALBP (A) RP-HPLC ultraviolet profile, (B) reconstructed total ion current, and (C) electrospray mass spectrum with the deconvoluted spectrum shown m the inset LCMS analysis of nonfusion human rCRALBP (1.5 p,g) was performed as described in the legend to Fig. 3, yielding a measured protein mass of = 36,347 4 (calculated = 36,343). 

Figure 10.4 All spectra obtained between 20 and 66 minutes are combined into a single spectrum and then deconvoluted using MaxEnt 1. The resulting molecular weight spectrum is noisy and hampers the identification of low abundance proteins. The asterisks indicate where proteins of mass 7274 and 10652 should be observed but are not.

Figure 10.6 Single representative cellular protein spectrum of E. coli K12 generated by deconvoluting the spectra in 30-second intervals from 20 minutes to 66 minutes. The asterisks indicate where proteins of mass 7274 and 10,652 are observed.

Because online separations provide such a wealth of information about target proteins, interpretation becomes of critical importance in order to make full use of the data. The first step in any analysis of LC-MS data involves integration and deconvolution of sample spectra to determine protein mass and intensity. In manual analysis (Hamler et al., 2004), users identify protein umbrellas, create a total ion chromatogram (TIC), integrate the protein peak, and deconvolute the resulting spectrum. Deconvolution of ESI spectra employs a maximum entropy deconvolution algorithm often referred to as MaxEnt (Ferrige et al., 1991). MaxEnt calculates... 

The central engine of this data workflow is the process of spectral deconvolution. During spectral deconvolution, sets of multiply charged ions associated with particular proteins are reduced to a simplified spectrum representing the neutral mass forms of those proteins. Our laboratory makes use of a maximum entropy-based approach to spectral deconvolution (Ferrige et al., 1992a and b) that attempts to identify the most likely distribution of neutral masses that accounts for all data within the m/z mass spectrum. With this approach, quantitative peak intensity information is retained from the source spectrum, and meaningful intensity differences can be obtained by comparison of LC/MS runs acquired and processed under similar conditions. 

As we optimized Tethering we used a variety of mass spectrometers. In our experience, the sensitivity and high resolution of TOP analyzers has provided the most rapid and accurate analyses of intact proteins. An example of an ESI-TOF data set from a standard experiment is illustrated in Fig. 9.2. Figure 9.2A is the deconvoluted mass spectrum of a Cys-mutant target protein after equilibration... 

If the protein molecular weight is unknown, then the charge states are also not known. The process of determining the molecular weight for an unknown protein from such a mass spectrum is known as deconvolution and is based on simple algebra. If MW is the... 

A widely used approach to extract information on protein secondary structure from infrared spectra is linked to computational techniques of Fourier deconvolution. These methods decrease the widths of infrared bands, allowing for increased separation and thus better identification of overlapping component bands present under the composite wide contour in the measured spectra [705]. Increased separation can also be achieved by calculating the nth derivative of the absorption spectrum, either in the frequency domain or though mathematical manipulations in the Fourier domain [114], An example is the method of Susi [775] which uses second derivative FT-IR spectra recorded in D20 for comparison with similar spectra derived from proteins with known structure. These methods have not yielded quantitative results that are more accurate than those obtained with methods that do not use deconvolution. 

Deconvolution of an ESI spectrum of a protein mixture. From Finnigan documentation. Reprinted, with permission. 

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