A pipeline to translate glycosaminoglycan sequences into 3D models. Application to the exploration of glycosaminoglycan conformational space.
Journal
Glycobiology
ISSN: 1460-2423
Titre abrégé: Glycobiology
Pays: England
ID NLM: 9104124
Informations de publication
Date de publication:
01 01 2019
01 01 2019
Historique:
received:
13
06
2018
accepted:
16
09
2018
pubmed:
22
9
2018
medline:
29
3
2019
entrez:
22
9
2018
Statut:
ppublish
Résumé
Mammalian glycosaminoglycans are linear complex polysaccharides comprising heparan sulfate, heparin, dermatan sulfate, chondroitin sulfate, keratan sulfate and hyaluronic acid. They bind to numerous proteins and these interactions mediate their biological activities. GAG-protein interaction data reported in the literature are curated mostly in MatrixDB database (http://matrixdb.univ-lyon1.fr/). However, a standard nomenclature and a machine-readable format of GAGs together with bioinformatics tools for mining these interaction data are lacking. We report here the building of an automated pipeline to (i) standardize the format of GAG sequences interacting with proteins manually curated from the literature, (ii) translate them into the machine-readable GlycoCT format and into SNFG (Symbol Nomenclature For Glycan) images and (iii) convert their sequences into a format processed by a builder generating three-dimensional structures of polysaccharides based on a repertoire of conformations experimentally validated by data extracted from crystallized GAG-protein complexes. We have developed for this purpose a converter (the CT23D converter) to automatically translate the GlycoCT code of a GAG sequence into the input file required to construct a three-dimensional model.
Identifiants
pubmed: 30239692
pii: 5099147
doi: 10.1093/glycob/cwy084
doi:
Substances chimiques
Glycosaminoglycans
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM