<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Hever H</submitter><funding>Nemzeti Kutat?si, Fejleszt?si ?s Innovaci?s Alap</funding><pagination>333-343</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC10853973</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>35(2)</volume><pubmed_abstract>High confidence and reproducibility are still challenges in bottom-up mass spectrometric &lt;i>N&lt;/i>-glycopeptide identification. The collision energy used in the MS/MS measurements and the database search engine used to identify the species are perhaps the two most decisive factors. We investigated how the structural features of &lt;i>N&lt;/i>-glycopeptides and the choice of the search engine influence the optimal collision energy, delivering the highest identification confidence. We carried out LC-MS/MS measurements using a series of collision energies on a large set of &lt;i>N&lt;/i>-glycopeptides with both the glycan and peptide part varied and studied the behavior of Byonic, pGlyco, and GlycoQuest scores. We found that search engines show a range of behavior between peptide-centric and glycan-centri</pubmed_abstract><journal>Journal of the American Society for Mass Spectrometry</journal><pubmed_title>Can We Boost &lt;i>N&lt;/i>-Glycopeptide Identification Confidence? Smart Collision Energy Choice Taking into Account Structure and Search Engine.</pubmed_title><pmcid>PMC10853973</pmcid><funding_grant_id>PD-132135</funding_grant_id><funding_grant_id>FK-138678</funding_grant_id><funding_grant_id>K-131762</funding_grant_id><pubmed_authors>Nagy K</pubmed_authors><pubmed_authors>Komka K</pubmed_authors><pubmed_authors>Hever H</pubmed_authors><pubmed_authors>Xue A</pubmed_authors><pubmed_authors>Revesz A</pubmed_authors><pubmed_authors>Vekey K</pubmed_authors><pubmed_authors>Drahos L</pubmed_authors></additional><is_claimable>false</is_claimable><name>Can We Boost &lt;i>N&lt;/i>-Glycopeptide Identification Confidence? Smart Collision Energy Choice Taking into Account Structure and Search Engine.</name><description>High confidence and reproducibility are still challenges in bottom-up mass spectrometric &lt;i>N&lt;/i>-glycopeptide identification. The collision energy used in the MS/MS measurements and the database search engine used to identify the species are perhaps the two most decisive factors. We investigated how the structural features of &lt;i>N&lt;/i>-glycopeptides and the choice of the search engine influence the optimal collision energy, delivering the highest identification confidence. We carried out LC-MS/MS measurements using a series of collision energies on a large set of &lt;i>N&lt;/i>-glycopeptides with both the glycan and peptide part varied and studied the behavior of Byonic, pGlyco, and GlycoQuest scores. We found that search engines show a range of behavior between peptide-centric and glycan-centri</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Feb</publication><modification>2025-04-04T13:34:05.468Z</modification><creation>2025-04-04T13:34:05.468Z</creation></dates><accession>S-EPMC10853973</accession><cross_references><pubmed>38286027</pubmed><doi>10.1021/jasms.3c00375</doi></cross_references></HashMap>