Integrated Post-Experiment Monoisotopic Mass Refinement: An Integrated Approach to Accurately Assign Monoisotopic Precursor Masses to Tandem Mass Spectrometric Data
- Authors
 - Jung, Hee-Jung; Purvine, Samuel O.; Kim, Hokeun; Petyuk, Vladislav A.; Hyung, Seok-Won; Monroe, Matthew E.; Mun, Dong-Gi; Kim, Kyong-Chul; Park, Jong-Moon; Kim, Su-Jin; Tolic, Nikola; Slysz, Gordon W.; Moore, Ronald J.; Zhao, Rui; Adkins, Joshua N.; Anderson, Gordon A.; Lee, Hookeun; Camp, David G., II; Yu, Myeong-Hee; Smith, Richard D.; Lee, Sang-Won
 
- Issue Date
 - 2010-10-15
 
- Publisher
 - AMER CHEMICAL SOC
 
- Citation
 - ANALYTICAL CHEMISTRY, v.82, no.20, pp.8510 - 8518
 
- Abstract
 - Accurate assignment of monoisotopic precursor masses to tandem mass spectrometric (MS/MS) data is a fundamental and critically important step for successful peptide identifications in mass spectrometry based proteomics. Here we describe an integrated approach that combines three previously reported methods of treating MS/MS data for precursor mass refinement. This combined method, "integrated post-experiment monoisotopic mass refinement" (iPE-MMR), integrates steps (1) generation of refined MS/MS data by DeconMSn; (2) additional refinement of the resultant MS/MS data by a modified version of PE-MMR; and (3) elimination of systematic errors of precursor masses using DtaRefinery. iPE-MMR is the first method that utilizes all MS information from multiple MS scans of a precursor ion including multiple charge states, in an MS scan, to determine precursor mass. With the combination of these methods, iPE-MMR increases sensitivity in peptide identification and provides increased accuracy when applied to complex high-throughput proteomics data.
 
- Keywords
 - PEPTIDE IDENTIFICATION RATES; PROTEIN IDENTIFICATIONS; PROTEOMIC ANALYSES; HIGH-THROUGHPUT; SOFTWARE TOOL; SPECTRA; DEAMIDATION; ELIMINATION; ALGORITHM; ERRORS; PEPTIDE IDENTIFICATION RATES; PROTEIN IDENTIFICATIONS; PROTEOMIC ANALYSES; HIGH-THROUGHPUT; SOFTWARE TOOL; SPECTRA; DEAMIDATION; ELIMINATION; ALGORITHM; ERRORS
 
- ISSN
 - 0003-2700
 
- URI
 - https://pubs.kist.re.kr/handle/201004/130998
 
- DOI
 - 10.1021/ac101388b
 
- Appears in Collections:
 - KIST Article > 2010
 
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