A universal algorithm for fast and automated charge state deconvolution of electrospray mass-to-charge ratio spectra

Zhang, Zhongqi; Marshall, Alan G.

doi:10.1016/s1044-0305(97)00284-5

Cited by 497 publications

(452 citation statements)

References 18 publications

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“…MS/MS experiments were performed by detecting the parent ions with a peak width of 2-4 m/z values and by using 40% of the maximum activation amplitude. Average ESI mass spectra deconvolution was automatically performed with the software provided by Deca-XP instrument (Bioworks Browser) or MagTran 1.0 software (32). Experimental mass values were compared with the average theoretical mass values using a PeptideMass program available at the Swiss-Prot (http://us.expasy.org/tools) data bank.…”

Section: Rp-hplc Esi-ms and Ms/ms Analysismentioning

confidence: 99%

Enzymatic processing of β‐dystroglycan recombinant ectodomain by MMP‐9: Identification of the main cleavage site

et al. 2009

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SummaryDystroglycan (DG) is a membrane receptor belonging to the complex of glycoproteins associated to dystrophin. DG is formed by two subunits, a-DG, a highly glycosylated extracellular matrix protein, and b-DG, a transmembrane protein. The two DG subunits interact through the C-terminal domain of a-DG and the N-terminal extracellular domain of b-DG in a noncovalent way. Such interaction is crucial to maintain the integrity of the plasma membrane. In some pathological conditions, the interaction between the two DG subunits may be disrupted by the proteolytic activity of gelatinases (i.e. MMP-9 and/or MMP-2) that removes a portion or the whole b-DG ectodomain producing a 30 kDa truncated form of b-DG. However, the molecular mechanism underlying this event is still unknown. In this study, we carried out proteolysis of the recombinant extracellular domain of b-DG, b-DG(654-750) with human MMP-9, characterizing the catalytic parameters of its cleavage. Furthermore, using a combined approach based on SDS-PAGE, MALDI-TOF and HPLC-ESI-IT mass spectrometry, we were able to identify one main MMP-9 cleavage site that is localized between the amino acids His-715 and Leu-716 of b-DG, and we analysed the proteolytic fragments of b-DG(654-750) produced by MMP-9 enzymatic activity.

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Section: Rp-hplc Esi-ms and Ms/ms Analysismentioning

confidence: 99%

Enzymatic processing of β‐dystroglycan recombinant ectodomain by MMP‐9: Identification of the main cleavage site

et al. 2009

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“…While some instrument manufacturers have developed reasonably effective programs for this problem, they rarely publish these algorithms, and thus the strengths and limitations of these methods are difficult or impossible to assess. Hence, there is need for the development of advanced data analysis algorithms [15][16][17][18][19][20][21]. In this work, several new algorithms are discussed that allow for the improved automated reduction of high-resolution mass spectra into a monoisotopic peak list.…”

Section: T He Wide Employment Of Fourier Transform Massmentioning

confidence: 99%

“…Since the same mass can have multiple charge states and there can be multiple isotopic peaks at each nominal m/z value, a very dense, complicated spectrum can be generated. The first attempt for automated spectrum interpretation was (somewhat erroneously) called "deconvolution" [15][16][17]20]. "Deconvolution" was based upon the principle that charge states can take only integer values.…”

Section: T He Wide Employment Of Fourier Transform Massmentioning

confidence: 99%

“…Furthermore, these methods generally perform poorly with low S/N and complex spectra resulting in missed peaks (false negatives). Also, most "deconvolution" methods bias against peaks represented by only one charge state which will be poorly represented in these deconvolution approaches, though the Z score [20] algorithm does not suffer from this drawback.…”

Section: T He Wide Employment Of Fourier Transform Massmentioning

confidence: 99%

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Algorithms for automatic interpretation of high resolution mass spectra

Kaur

O’Connor

2006

J. Am. Soc. Mass Spectrom.

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Automated interpretation of high-resolution mass spectra in a reliable and efficient manner represents a highly challenging computational problem. This work aims at developing methods for reducing a high-resolution mass spectrum into its monoisotopic peak list, and automatically assigning observed masses to known fragment ion masses if the protein sequence is available. The methods are compiled into a suite of data reduction algorithms which is called MasSPIKE (Mass Spectrum Interpretation and Kernel Extraction). MasSPIKE includes modules for modeling noise across the spectrum, isotopic cluster identification, charge state determination, separation of overlapping isotopic distributions, picking isotopic peaks, aligning experimental and theoretical isotopic distributions for estimating a monoisotopic peak's location, generating the monoisotopic mass list, and assigning the observed monoisotopic masses to possible protein fragments. The method is tested against a complex top-down spectrum of bovine carbonic anhydrase. Results of each of the individual modules are compared with previously published work. (J Am Soc Mass Spectrom 2006, 17, 459 -468)

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“…The resolution of mixture components with modest differences in their mass/charge ratios can became impossible, due to the m/z scale compression. Algorithms that allow the deconvolution of overlapping charge states distributionthereby facilitating the identification of mixture components-have been proposed (Mann, Meng, & Fenn, 1989;Zhang & Marshall, 1998). However, as spectral complexity and chemical noise levels increase, those algorithms are likely to produce artifactual peaks and might also miss analyte peaks with a low signal intensity.…”

Section: Multicharge Effectmentioning

confidence: 99%

Development of new methodologies for the mass spectrometry study of bioorganic macromolecules

Cristoni

Bernardi

2003

Mass Spectrometry Reviews

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I. Introduction 370 II. Techniques That Are Usually Employed in the Study of Bioorganic Macromolecules 371 A. Proteins and Peptides 371 B. Oligonucleotides 374 C. Oligosaccharides and Glycoconjugates 375 D. Various Complexes (DNA–Protein, Antigen–Antibody, Macromolecules–Metals) 377 III. Common Problems and Developments in the Analysis of Bioorganic Macromolecules by Mass Spectrometry 377 A. Ionization Source Problems and Developments 377 1. Sensitivity 377 2. Problems with Buffers 379 3. Multicharge Effect 381 B. Mass Analyzer Problems and Developments 381 1. Linear Dynamic Range 381 2. Tandem Mass Spectrometry 382 3. Sensitivity 382 4. Resolution 383 5. Mass Accuracy 383 IV. New Promising Technologies 384 A. Interfaces and Ionization Sources 384 1. Improvements in the Coupling of Liquid‐Phase Separation Systems to Mass Spectrometry 384 2. AP‐MALDI 384 3. Deprotonant Agents 385 4. Sonic Spray Ionization 388 5. APCI without Corona Discharge 391 B. Mass Analyzers 393 1. Linear Quadrupole Ion Trap 394 2. TOF Analyzers with New Detectors 395 3. Multiple Mass Analyzers 396 V. Software for Data Treatment 397 VI. Conclusions and Future Developments 399 Acknowledgments 400 References 400 In recent years, mass spectrometry has been increasingly used for the analysis of various macromolecules of biological, biomedical, and biochemical interest. This increase has been made possible by two key developments: the advent of electrospray ionization (ESI) and matrix‐assisted laser desorption ionization (MALDI) sources. The two new techniques produce a significant increase in mass range and in sensitivity that led to the development of new applications and of new analyzer designs, software, and robotics. This review, apart from the description of the status of mass spectrometry in the analysis of bioorganic macromolecules, is mainly devoted to the illustration of the more recent promising techniques and on their possible future evolution. © 2003 Wiley Periodicals, Inc., Mass Spec Rev 22:369–406, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mas.10062

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A universal algorithm for fast and automated charge state deconvolution of electrospray mass-to-charge ratio spectra

Cited by 497 publications

References 18 publications

Enzymatic processing of β‐dystroglycan recombinant ectodomain by MMP‐9: Identification of the main cleavage site

Enzymatic processing of β‐dystroglycan recombinant ectodomain by MMP‐9: Identification of the main cleavage site

Algorithms for automatic interpretation of high resolution mass spectra

Development of new methodologies for the mass spectrometry study of bioorganic macromolecules

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