Monoisotopic mass determination algorithm for selenocysteine-containing polypeptides from mass spectrometric data based on theoretical modeling of isotopic peak intensity ratios.
Identifieur interne : 000842 ( Main/Exploration ); précédent : 000841; suivant : 000843Monoisotopic mass determination algorithm for selenocysteine-containing polypeptides from mass spectrometric data based on theoretical modeling of isotopic peak intensity ratios.
Auteurs : Jin Wook Kim [Corée du Sud] ; Sunho Lee ; Kunsoo Park ; Seungjin Na ; Eunok Paek ; Hyung Seo Park ; Heejin Park ; Kong-Joo Lee ; Jaeho Jeong ; Hwa-Young KimSource :
- Journal of proteome research [ 1535-3907 ] ; 2012.
Descripteurs français
- KwdFr :
- Algorithmes (MeSH), Données de séquences moléculaires (MeSH), Isotopes (composition chimique), Modèles chimiques (MeSH), Peptides (composition chimique), Spectrométrie de masse (méthodes), Sélénocystéine (composition chimique), Sélénoprotéines (composition chimique), Séquence d'acides aminés (MeSH).
- MESH :
- composition chimique : Isotopes, Peptides, Sélénocystéine, Sélénoprotéines.
- méthodes : Spectrométrie de masse.
- Algorithmes, Données de séquences moléculaires, Modèles chimiques, Séquence d'acides aminés.
English descriptors
- KwdEn :
- MESH :
- chemical , chemistry : Isotopes, Peptides, Selenocysteine, Selenoproteins.
- methods : Mass Spectrometry.
- Algorithms, Amino Acid Sequence, Models, Chemical, Molecular Sequence Data.
Abstract
Selenoproteins, containing selenocysteine (Sec, U) as the 21st amino acid in the genetic code, are well conserved from bacteria to human, except yeast and higher plants that miss the Sec insertion machinery. Determination of Sec association is important to find substrates and to understand redox action of selenoproteins. While mass spectrometry (MS) has become a common and powerful tool to determine an amino acid sequence of a protein, identification of a protein sequence containing Sec was not easy using MS because of the limited stability of Sec in selenoproteins. Se has six naturally occurring isotopes, ⁷⁴Se, ⁷⁶Se, ⁷⁷Se, ⁷⁸Se, ⁸⁰Se, and ⁸²Se, and ⁸⁰Se is the most abundant isotope. These characteristics provide a good indicator for selenopeptides but make it difficult to detect selenopeptides using software analysis tools developed for common peptides. Thus, previous reports verified MS scans of selenopeptides by manual inspection. None of the fully automated algorithms have taken into account the isotopes of Se, leading to the wrong interpretation for selenopeptides. In this paper, we present an algorithm to determine monoisotopic masses of selenocysteine-containing polypeptides. Our algorithm is based on a theoretical model for an isotopic distribution of a selenopeptide, which regards peak intensities in an isotopic distribution as the natural abundances of C, H, N, O, S, and Se. Our algorithm uses two kinds of isotopic peak intensity ratios: one for two adjacent peaks and another for two distant peaks. It is shown that our algorithm for selenopeptides performs accurately, which was demonstrated with two LC-MS/MS data sets. Using this algorithm, we have successfully identified the Sec-Cys and Sec-Sec cross-linking of glutaredoxin 1 (GRX1) from mass spectra obtained by UPLC-ESI-q-TOF instrument.
DOI: 10.1021/pr300232y
PubMed: 22779694
Affiliations:
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Kunsoo" uniqKey="Park K" first="Kunsoo" last="Park">Kunsoo Park</name></author><author><name sortKey="Na, Seungjin" sort="Na, Seungjin" uniqKey="Na S" first="Seungjin" last="Na">Seungjin Na</name></author><author><name sortKey="Paek, Eunok" sort="Paek, Eunok" uniqKey="Paek E" first="Eunok" last="Paek">Eunok Paek</name></author><author><name sortKey="Park, Hyung Seo" sort="Park, Hyung Seo" uniqKey="Park H" first="Hyung Seo" last="Park">Hyung Seo Park</name></author><author><name sortKey="Park, Heejin" sort="Park, Heejin" uniqKey="Park H" first="Heejin" last="Park">Heejin Park</name></author><author><name sortKey="Lee, Kong Joo" sort="Lee, Kong Joo" uniqKey="Lee K" first="Kong-Joo" last="Lee">Kong-Joo Lee</name></author><author><name sortKey="Jeong, Jaeho" sort="Jeong, Jaeho" uniqKey="Jeong J" first="Jaeho" last="Jeong">Jaeho Jeong</name></author><author><name sortKey="Kim, Hwa Young" sort="Kim, Hwa Young" uniqKey="Kim H" first="Hwa-Young" last="Kim">Hwa-Young 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wicri:level="1"><nlm:affiliation>Medical Information Center, Seoul National University Hospital, Seoul 110-744, Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Medical Information Center, Seoul National University Hospital, Seoul 110-744</wicri:regionArea><placeName><settlement type="city">Séoul</settlement><region type="capital">Région capitale de Séoul</region></placeName></affiliation></author><author><name sortKey="Lee, Sunho" sort="Lee, Sunho" uniqKey="Lee S" first="Sunho" last="Lee">Sunho Lee</name></author><author><name sortKey="Park, Kunsoo" sort="Park, Kunsoo" uniqKey="Park K" first="Kunsoo" last="Park">Kunsoo Park</name></author><author><name sortKey="Na, Seungjin" sort="Na, Seungjin" uniqKey="Na S" first="Seungjin" last="Na">Seungjin Na</name></author><author><name sortKey="Paek, Eunok" sort="Paek, Eunok" uniqKey="Paek E" first="Eunok" last="Paek">Eunok Paek</name></author><author><name sortKey="Park, Hyung Seo" sort="Park, Hyung Seo" uniqKey="Park H" first="Hyung Seo" last="Park">Hyung Seo Park</name></author><author><name sortKey="Park, Heejin" sort="Park, Heejin" uniqKey="Park H" first="Heejin" last="Park">Heejin Park</name></author><author><name sortKey="Lee, Kong Joo" sort="Lee, Kong Joo" uniqKey="Lee K" first="Kong-Joo" last="Lee">Kong-Joo Lee</name></author><author><name sortKey="Jeong, Jaeho" sort="Jeong, Jaeho" uniqKey="Jeong J" first="Jaeho" last="Jeong">Jaeho Jeong</name></author><author><name sortKey="Kim, Hwa Young" sort="Kim, Hwa Young" uniqKey="Kim H" first="Hwa-Young" last="Kim">Hwa-Young Kim</name></author></analytic><series><title level="j">Journal of proteome research</title><idno type="eISSN">1535-3907</idno><imprint><date when="2012" type="published">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms (MeSH)</term><term>Amino Acid Sequence (MeSH)</term><term>Isotopes (chemistry)</term><term>Mass Spectrometry (methods)</term><term>Models, Chemical (MeSH)</term><term>Molecular Sequence Data (MeSH)</term><term>Peptides (chemistry)</term><term>Selenocysteine (chemistry)</term><term>Selenoproteins (chemistry)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes (MeSH)</term><term>Données de séquences moléculaires (MeSH)</term><term>Isotopes (composition chimique)</term><term>Modèles chimiques (MeSH)</term><term>Peptides (composition chimique)</term><term>Spectrométrie de masse (méthodes)</term><term>Sélénocystéine (composition chimique)</term><term>Sélénoprotéines (composition chimique)</term><term>Séquence d'acides aminés (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="chemistry" xml:lang="en"><term>Isotopes</term><term>Peptides</term><term>Selenocysteine</term><term>Selenoproteins</term></keywords><keywords scheme="MESH" qualifier="composition chimique" xml:lang="fr"><term>Isotopes</term><term>Peptides</term><term>Sélénocystéine</term><term>Sélénoprotéines</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Mass Spectrometry</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Spectrométrie de masse</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Amino Acid Sequence</term><term>Models, Chemical</term><term>Molecular Sequence Data</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Données de séquences moléculaires</term><term>Modèles chimiques</term><term>Séquence d'acides aminés</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Selenoproteins, containing selenocysteine (Sec, U) as the 21st amino acid in the genetic code, are well conserved from bacteria to human, except yeast and higher plants that miss the Sec insertion machinery. Determination of Sec association is important to find substrates and to understand redox action of selenoproteins. While mass spectrometry (MS) has become a common and powerful tool to determine an amino acid sequence of a protein, identification of a protein sequence containing Sec was not easy using MS because of the limited stability of Sec in selenoproteins. Se has six naturally occurring isotopes, ⁷⁴Se, ⁷⁶Se, ⁷⁷Se, ⁷⁸Se, ⁸⁰Se, and ⁸²Se, and ⁸⁰Se is the most abundant isotope. These characteristics provide a good indicator for selenopeptides but make it difficult to detect selenopeptides using software analysis tools developed for common peptides. Thus, previous reports verified MS scans of selenopeptides by manual inspection. None of the fully automated algorithms have taken into account the isotopes of Se, leading to the wrong interpretation for selenopeptides. In this paper, we present an algorithm to determine monoisotopic masses of selenocysteine-containing polypeptides. Our algorithm is based on a theoretical model for an isotopic distribution of a selenopeptide, which regards peak intensities in an isotopic distribution as the natural abundances of C, H, N, O, S, and Se. Our algorithm uses two kinds of isotopic peak intensity ratios: one for two adjacent peaks and another for two distant peaks. It is shown that our algorithm for selenopeptides performs accurately, which was demonstrated with two LC-MS/MS data sets. Using this algorithm, we have successfully identified the Sec-Cys and Sec-Sec cross-linking of glutaredoxin 1 (GRX1) from mass spectra obtained by UPLC-ESI-q-TOF instrument.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">22779694</PMID><DateCompleted><Year>2013</Year><Month>03</Month><Day>28</Day></DateCompleted><DateRevised><Year>2013</Year><Month>11</Month><Day>21</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1535-3907</ISSN><JournalIssue CitedMedium="Internet"><Volume>11</Volume><Issue>9</Issue><PubDate><Year>2012</Year><Month>Sep</Month><Day>07</Day></PubDate></JournalIssue><Title>Journal of proteome research</Title><ISOAbbreviation>J Proteome Res</ISOAbbreviation></Journal><ArticleTitle>Monoisotopic mass determination algorithm for selenocysteine-containing polypeptides from mass spectrometric data based on theoretical modeling of isotopic peak intensity ratios.</ArticleTitle><Pagination><MedlinePgn>4488-98</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1021/pr300232y</ELocationID><Abstract><AbstractText>Selenoproteins, containing selenocysteine (Sec, U) as the 21st amino acid in the genetic code, are well conserved from bacteria to human, except yeast and higher plants that miss the Sec insertion machinery. Determination of Sec association is important to find substrates and to understand redox action of selenoproteins. While mass spectrometry (MS) has become a common and powerful tool to determine an amino acid sequence of a protein, identification of a protein sequence containing Sec was not easy using MS because of the limited stability of Sec in selenoproteins. Se has six naturally occurring isotopes, ⁷⁴Se, ⁷⁶Se, ⁷⁷Se, ⁷⁸Se, ⁸⁰Se, and ⁸²Se, and ⁸⁰Se is the most abundant isotope. These characteristics provide a good indicator for selenopeptides but make it difficult to detect selenopeptides using software analysis tools developed for common peptides. Thus, previous reports verified MS scans of selenopeptides by manual inspection. None of the fully automated algorithms have taken into account the isotopes of Se, leading to the wrong interpretation for selenopeptides. In this paper, we present an algorithm to determine monoisotopic masses of selenocysteine-containing polypeptides. Our algorithm is based on a theoretical model for an isotopic distribution of a selenopeptide, which regards peak intensities in an isotopic distribution as the natural abundances of C, H, N, O, S, and Se. Our algorithm uses two kinds of isotopic peak intensity ratios: one for two adjacent peaks and another for two distant peaks. It is shown that our algorithm for selenopeptides performs accurately, which was demonstrated with two LC-MS/MS data sets. Using this algorithm, we have successfully identified the Sec-Cys and Sec-Sec cross-linking of glutaredoxin 1 (GRX1) from mass spectra obtained by UPLC-ESI-q-TOF instrument.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Kim</LastName><ForeName>Jin Wook</ForeName><Initials>JW</Initials><AffiliationInfo><Affiliation>Medical Information Center, Seoul National University Hospital, Seoul 110-744, Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lee</LastName><ForeName>Sunho</ForeName><Initials>S</Initials></Author><Author ValidYN="Y"><LastName>Park</LastName><ForeName>Kunsoo</ForeName><Initials>K</Initials></Author><Author ValidYN="Y"><LastName>Na</LastName><ForeName>Seungjin</ForeName><Initials>S</Initials></Author><Author ValidYN="Y"><LastName>Paek</LastName><ForeName>Eunok</ForeName><Initials>E</Initials></Author><Author ValidYN="Y"><LastName>Park</LastName><ForeName>Hyung Seo</ForeName><Initials>HS</Initials></Author><Author ValidYN="Y"><LastName>Park</LastName><ForeName>Heejin</ForeName><Initials>H</Initials></Author><Author ValidYN="Y"><LastName>Lee</LastName><ForeName>Kong-Joo</ForeName><Initials>KJ</Initials></Author><Author ValidYN="Y"><LastName>Jeong</LastName><ForeName>Jaeho</ForeName><Initials>J</Initials></Author><Author ValidYN="Y"><LastName>Kim</LastName><ForeName>Hwa-Young</ForeName><Initials>HY</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2012</Year><Month>08</Month><Day>13</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>J Proteome Res</MedlineTA><NlmUniqueID>101128775</NlmUniqueID><ISSNLinking>1535-3893</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D007554">Isotopes</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D010455">Peptides</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D051140">Selenoproteins</NameOfSubstance></Chemical><Chemical><RegistryNumber>0CH9049VIS</RegistryNumber><NameOfSubstance UI="D017279">Selenocysteine</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000465" MajorTopicYN="Y">Algorithms</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000595" MajorTopicYN="N">Amino Acid Sequence</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007554" MajorTopicYN="N">Isotopes</DescriptorName><QualifierName UI="Q000737" MajorTopicYN="N">chemistry</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D013058" MajorTopicYN="N">Mass Spectrometry</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008956" MajorTopicYN="Y">Models, Chemical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008969" MajorTopicYN="N">Molecular Sequence Data</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010455" MajorTopicYN="N">Peptides</DescriptorName><QualifierName UI="Q000737" MajorTopicYN="Y">chemistry</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D017279" MajorTopicYN="N">Selenocysteine</DescriptorName><QualifierName UI="Q000737" MajorTopicYN="Y">chemistry</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D051140" MajorTopicYN="N">Selenoproteins</DescriptorName><QualifierName UI="Q000737" MajorTopicYN="Y">chemistry</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2012</Year><Month>7</Month><Day>12</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2012</Year><Month>7</Month><Day>12</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2013</Year><Month>3</Month><Day>30</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">22779694</ArticleId><ArticleId IdType="doi">10.1021/pr300232y</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Corée du Sud</li></country><region><li>Région capitale de Séoul</li></region><settlement><li>Séoul</li></settlement></list><tree><noCountry><name sortKey="Jeong, Jaeho" sort="Jeong, Jaeho" uniqKey="Jeong J" first="Jaeho" last="Jeong">Jaeho Jeong</name><name sortKey="Kim, Hwa Young" sort="Kim, Hwa Young" uniqKey="Kim H" first="Hwa-Young" last="Kim">Hwa-Young Kim</name><name sortKey="Lee, Kong Joo" sort="Lee, Kong Joo" uniqKey="Lee K" first="Kong-Joo" last="Lee">Kong-Joo Lee</name><name sortKey="Lee, Sunho" sort="Lee, Sunho" uniqKey="Lee S" first="Sunho" last="Lee">Sunho Lee</name><name sortKey="Na, Seungjin" sort="Na, Seungjin" uniqKey="Na S" first="Seungjin" last="Na">Seungjin Na</name><name sortKey="Paek, Eunok" sort="Paek, Eunok" uniqKey="Paek E" first="Eunok" last="Paek">Eunok Paek</name><name sortKey="Park, Heejin" sort="Park, Heejin" uniqKey="Park H" first="Heejin" last="Park">Heejin Park</name><name sortKey="Park, Hyung Seo" sort="Park, Hyung Seo" uniqKey="Park H" first="Hyung Seo" last="Park">Hyung Seo Park</name><name sortKey="Park, Kunsoo" sort="Park, Kunsoo" uniqKey="Park K" first="Kunsoo" last="Park">Kunsoo Park</name></noCountry><country name="Corée du Sud"><region name="Région capitale de Séoul"><name sortKey="Kim, Jin Wook" 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