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PXD054730

PXD054730 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleRemoval of NHS-labelling by-products in proteomic samples
DescriptionN-Hydroxysuccinimide (NHS) chemistry is used extensively across proteomics sample preparation. One of the most popular applications is its use in isobaric reagent based quantitation; specifically both the iTRAQ and TMT approaches. The labels are introduced onto primary Serines, tyrosines, and threonines can be labelled during TMT labelling reactions in addition to the desired amides. These peptides are typically classed as over-labelled and are disregarded for quantification. Their presence also unnecessarily increases sample complexity, which reduces identification rates. In this study, we developed a robust method to remove over-labelled peptides through systematic screening of nucleophilic aminolysis reagents and reaction conditions. The new method reduces the proportion of over-labelled peptides in the sample to less than 1% without affecting the labelling rate or introducing other modifications, leading to superior identification rates and quantitation precision.
HostingRepositoryPRIDE
AnnounceDate2025-03-14
AnnouncementXMLSubmission_2025-03-14_06:58:25.565.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterYana Demyanenko
SpeciesList scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationListTMT6plex reporter+balance reagent acylated residue; iodoacetamide derivatized residue
InstrumentOrbitrap Ascend
Dataset History
RevisionDatetimeStatusChangeLog Entry
02024-08-08 15:51:34ID requested
12025-03-14 06:58:26announced
Publication List
10.1016/J.MCPRO.2025.100948;
Keyword List
submitter keyword: NHS, methylamine, hydroxylamine,N-hydroxysuccinimide, O-acylation
Contact List
Shabaz Mohammed
contact affiliationThe Rosalind Franklon Institute, University of Oxford
contact emailshabaz.mohammed@rfi.ac.uk
lab head
Yana Demyanenko
contact affiliationRosalind Franklin Institute
contact emailyana.demyanenko@rfi.ac.uk
dataset submitter
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Dataset FTP location
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