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Wolski, Witold; Farrow, Malcolm; Emde, Anne-Katrin; Lehrach, Hans; Łałowski, Maciej; Reinert, Knut

doi:10.1186/1477-5956-4-18

Cited by 25 publications

(33 citation statements)

References 36 publications

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“…However, during experimental work, the existence of the so called mass defect should be taken into account, which involves the difference between nominal calculated and experimentally determined monoisotopic masses. This difference increases linearly with an increase in the mass of the peptide and, according to various estimations, has a slope from 4.55 × 10 -4 [18] to 5.7 × 10 -4 [19] (on aver age, 4.99 × 10 -4 [20]). Thus, when working in the mass range from 1000 to 3000 Da, a measurement error of the mass of not less than ±1 Da should be introduced.…”

Section: Resultsmentioning

confidence: 94%

Theoretical possibilities and limitations of protease primary specificity determination by statistical analysis of MALDI mass-spectra of proteolysis products

2012

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Possibilities and limitations of the method of examination of proteolytic enzymes' primary spec ificity by statistical analysis of MALDI (matrix assisted laser desorption/ionization) mass spectra of products obtained by protein substrate proteolysis, without direct determination of their amino acid sequences, were investigated theoretically. The optimum range given by the measurement errors of the peptides' masses for obtaining a statistical set of the events, and the form of statistical data presentation, were chosen. It was shown that the proposed method can be applied only for proteases with a relatively narrow primary specificity (two or three amino acids). The influence of protein substrate molecular weight and amino acid composition on the efficiency of specifics for a particular protease amino acid, revealed under statistical treatment of the set of proteolysis product masses, was studied on the model of trypsin, chymotrypsin, glutamylendopeptidase, pepsin (pH 1.3).

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Section: Resultsmentioning

confidence: 94%

Theoretical possibilities and limitations of protease primary specificity determination by statistical analysis of MALDI mass-spectra of proteolysis products

2012

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“…For each peptide, feature file msInspect/AMT examined the association between each peptide's mass (as reported by the instrument) and distance to the nearest theoretical mass cluster. 13 For peptide feature files in which a linear relationship with nonzero slope is found (indicating calibration error), masses are readjusted. In this case, all six MS1 peptide feature files contained similar, highly significant deviations.…”

Section: Resultsmentioning

confidence: 99%

“…MsInspect/AMT generated the green lines in Figure 3, which identify peptides having individually estimated mass defect errors within 200 ppm, a tolerance recommended by Wolski. 13 We removed all peptides associated with points outside that region from each peptide feature file. Overall, we removed between 132 and 180 (mean: 154) peptides from each of the peptide feature files; see columns 3 and 6 of Table 1.…”

Section: Resultsmentioning

confidence: 99%

“…To ensure that masses are reported as accurately as possible in the presence of calibration error, we first recalibrate masses using a procedure that is based on an approach described by Wolski. 13 This approach recognizes that, when calibrated correctly, distances between peptides will form distinct, equidistantly spaced clusters due to their similar elemental composition. This cluster spacing is due to the fact that peptide masses are largely composed of nucleons which weigh roughly, but not exactly, one Dalton (not exactly, because of the effect of the mass defect, which varies from element to element).…”

Section: Part I: Normalization Of Lc-ms/ms Experiments Andmentioning

confidence: 99%

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A Platform for Accurate Mass and Time Analyses of Mass Spectrometry Data

et al. 2007

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We describe an integrated suite of algorithms and software for general accurate mass and time (AMT) tagging data analysis of mass spectrometry data. The AMT approach combines identifications from liquid chromatography (LC) tandem mass spectrometry (MS/MS) data with peptide accurate mass and retention time locations from high-resolution LC-MS data. Our workflow includes the traditional AMT approach, in which MS/MS identifications are located in external databases, as well as methods based on more recent hybrid instruments such as the LTQ-FT or Orbitrap, where MS/MS identifications are embedded with the MS data. We demonstrate our AMT workflow's utility for general data synthesis by combining data from two dissimilar biospecimens. Specifically, we demonstrate its use relevant to serum biomarker discovery by identifying which peptides sequenced by MS/MS analysis of tumor tissue may also be present in the plasma of tumor-bearing and control mice. The analysis workflow, referred to as msInspect/AMT, extends and combines existing open-source platforms for LC-MS/MS (CPAS) and LC-MS (msInspect) data analysis and is available in an unrestricted open-source distribution.

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“…Precursor and fragment masses are calculated from their observed m/z values and are each binned coarsely with bin size 1.0005079, corresponding to the distance between the centers of two adjacent peptide mass clusters. 9 One list of paired measurements is initialized for precursor values, and another for fragments.…”

Section: Methodsmentioning

confidence: 99%

Param-Medic: A Tool for Improving MS/MS Database Search Yield by Optimizing Parameter Settings

2017

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In shotgun proteomics analysis, user-specified parameters are critical to database search performance and therefore to the yield of confident peptide-spectrum matches (PSMs). Two of the most important parameters are related to the accuracy of the mass spectrometer. Precursor mass tolerance defines the peptide candidates considered for each spectrum. Fragment mass tolerance or bin size determines how close observed and theoretical fragments must be in order to be considered a match. For either of these two parameters, too wide a setting yields randomly high-scoring false PSMs, whereas too narrow a setting erroneously excludes true PSMs., in either case lowering the yield of peptides detected at a given false discovery rate. We describe a strategy for inferring optimal search parameters by assembling and analyzing pairs of spectra that are likely to have been generated by the same peptide ion in order to infer precursor and fragment mass error. This strategy does not rely on a database search, making it usable in a wide variety of settings. In our experiments, this strategy yields more high confidence PSMs than using settings based on instrument defaults or determined by experts. Param-Medic is open source and cross-platform. It is available as a standalone tool (http://noble.gs.washington.edu/proj/param-medic/) and has been integrated into the Crux proteomics toolkit (http://crux.ms), providing automatic parameter selection for the Comet and Tide search engines.

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Untitled

Cited by 25 publications

References 36 publications

Theoretical possibilities and limitations of protease primary specificity determination by statistical analysis of MALDI mass-spectra of proteolysis products

Theoretical possibilities and limitations of protease primary specificity determination by statistical analysis of MALDI mass-spectra of proteolysis products

A Platform for Accurate Mass and Time Analyses of Mass Spectrometry Data

Param-Medic: A Tool for Improving MS/MS Database Search Yield by Optimizing Parameter Settings

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