Expanding N-glycopeptide identifications by modeling fragmentation, elution, and glycome connectivity.
Nat Commun
; 15(1): 6168, 2024 Jul 22.
Article
en En
| MEDLINE
| ID: mdl-39039063
ABSTRACT
Accurate glycopeptide identification in mass spectrometry-based glycoproteomics is a challenging problem at scale. Recent innovation has been made in increasing the scope and accuracy of glycopeptide identifications, with more precise uncertainty estimates for each part of the structure. We present a dynamically adapting relative retention time model for detecting and correcting ambiguous glycan assignments that are difficult to detect from fragmentation alone, a layered approach to glycopeptide fragmentation modeling that improves N-glycopeptide identification in samples without compromising identification quality, and a site-specific method to increase the depth of the glycoproteome confidently identifiable even further. We demonstrate our techniques on a set of previously published datasets, showing the performance gains at each stage of optimization. These techniques are provided in the open-source glycomics and glycoproteomics platform GlycReSoft available at https//github.com/mobiusklein/glycresoft .
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Glicopéptidos
/
Proteómica
/
Glicómica
Límite:
Humans
Idioma:
En
Revista:
Nat Commun
Asunto de la revista:
BIOLOGIA
/
CIENCIA
Año:
2024
Tipo del documento:
Article
Pais de publicación:
Reino Unido