<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Guo Y</submitter><funding>NIGMS NIH HHS</funding><pagination>101873</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9587358</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>9</volume><pubmed_abstract>Isobaric chemical tag labeling for quantification of intact proteins in complex samples is limited due to the tendency of intact proteins precipitate under labeling conditions and increased sample complexity as a result of side products (&lt;i>i.e.&lt;/i>, incomplete labeling or labeling of unintended residues). To reduce precipitation under labeling conditions, we developed a technique to remove large proteoforms that allowed for the labeling and characterization of small proteoforms (&lt;35 kDa) using top-down proteomics. We also systematically optimized protein-level Tandem Mass Tag (TMT) labeling conditions to obtain optimal labeling parameters for complex samples. Here, we present a benchmarking protocol for protein-level TMT labeling for quantitative top-down proteomics, including complex int</pubmed_abstract><journal>MethodsX</journal><pubmed_title>A benchmarking protocol for intact protein-level Tandem Mass Tag (TMT) labeling for quantitative top-down proteomics.</pubmed_title><pmcid>PMC9587358</pmcid><funding_grant_id>R01 GM118470</funding_grant_id><pubmed_authors>Cupp-Sutton KA</pubmed_authors><pubmed_authors>Liu X</pubmed_authors><pubmed_authors>Guo Y</pubmed_authors><pubmed_authors>Wu S</pubmed_authors><pubmed_authors>Yu D</pubmed_authors></additional><is_claimable>false</is_claimable><name>A benchmarking protocol for intact protein-level Tandem Mass Tag (TMT) labeling for quantitative top-down proteomics.</name><description>Isobaric chemical tag labeling for quantification of intact proteins in complex samples is limited due to the tendency of intact proteins precipitate under labeling conditions and increased sample complexity as a result of side products (&lt;i>i.e.&lt;/i>, incomplete labeling or labeling of unintended residues). To reduce precipitation under labeling conditions, we developed a technique to remove large proteoforms that allowed for the labeling and characterization of small proteoforms (&lt;35 kDa) using top-down proteomics. We also systematically optimized protein-level Tandem Mass Tag (TMT) labeling conditions to obtain optimal labeling parameters for complex samples. Here, we present a benchmarking protocol for protein-level TMT labeling for quantitative top-down proteomics, including complex int</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022</publication><modification>2026-05-28T01:20:16.346Z</modification><creation>2025-02-18T23:29:48.653Z</creation></dates><accession>S-EPMC9587358</accession><cross_references><pubmed>36281278</pubmed><doi>10.1016/j.mex.2022.101873</doi></cross_references></HashMap>