Isotopic peak intensity ratio based algorithm for determination of isotopic clusters and monoisotopic masses of polypeptides from high-resolution mass spectrometric data
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Kunsoo | - |
dc.contributor.author | Yoon, Joo Young | - |
dc.contributor.author | Lee, Sunho | - |
dc.contributor.author | Paek, Eunok | - |
dc.contributor.author | Park, Heejin | - |
dc.contributor.author | Jung, Hee-Jung | - |
dc.contributor.author | Lee, Sang-Won | - |
dc.date.accessioned | 2021-09-09T03:46:31Z | - |
dc.date.available | 2021-09-09T03:46:31Z | - |
dc.date.created | 2021-06-10 | - |
dc.date.issued | 2008-10-01 | - |
dc.identifier.issn | 0003-2700 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/122583 | - |
dc.description.abstract | Determining isotopic clusters and their monoisotopic masses is a first step in interpreting complex mass spectra generated by high-resolution mass spectrometers. We propose a mathematical model for isotopic distributions of polypeptides and an effective interpretation algorithm. Our model uses two types of ratios: intensity ratio of two adjacent peaks and intensity ratio product of three adjacent peaks in an isotopic distribution. These ratios can be approximated as simple functions of a polypeptide mass, the values of which fall within certain ranges, depending on the polypeptide mass. Given a spectrum as a peak list, our algorithm first finds all isotopic clusters consisting of two or more peaks. Then, it scores clusters using the ranges of ratio functions and computes the monoisotopic masses of the identified clusters. Our method was applied to high-resolution mass spectra obtained from a Fourier transform ion cyclotron resonance (FTICR) mass spectrometer coupled to reverse-phase liquid chromatography (RPLC). For polypeptides whose amino acid sequences were identified by tandem mass spectrometry (MS/MS), we applied both THRASH-based software implementations and our method. Our method was observed to find more masses of known peptides when the numbers of the total clusters identified by both methods were fixed. Experimental results show that our method performed better for isotopic mass clusters of weak intensity where the isotopic distributions deviate significantly from their theoretical distributions. Also, it correctly identified some isotopic clusters that were not found by THRASH-based implementations, especially those for which THRASH gave 1 Da mismatches. Another advantage of our method is that it is very fast, much faster than THRASH that calculates the least-squares fit. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | AMER CHEMICAL SOC | - |
dc.subject | SPECTRA | - |
dc.subject | DECONVOLUTION | - |
dc.subject | DISTRIBUTIONS | - |
dc.title | Isotopic peak intensity ratio based algorithm for determination of isotopic clusters and monoisotopic masses of polypeptides from high-resolution mass spectrometric data | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Sang-Won | - |
dc.identifier.doi | 10.1021/ac800913b | - |
dc.identifier.scopusid | 2-s2.0-54749148348 | - |
dc.identifier.wosid | 000259603100018 | - |
dc.identifier.bibliographicCitation | ANALYTICAL CHEMISTRY, v.80, no.19, pp.7294 - 7303 | - |
dc.relation.isPartOf | ANALYTICAL CHEMISTRY | - |
dc.citation.title | ANALYTICAL CHEMISTRY | - |
dc.citation.volume | 80 | - |
dc.citation.number | 19 | - |
dc.citation.startPage | 7294 | - |
dc.citation.endPage | 7303 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Chemistry | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical | - |
dc.subject.keywordPlus | SPECTRA | - |
dc.subject.keywordPlus | DECONVOLUTION | - |
dc.subject.keywordPlus | DISTRIBUTIONS | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.