Toward Automatic Inference of Glycan Linkages Using MSⁿ and Machine Learning─Proof of Concept Using Sialic Acid Linkages.

ABSTRACT: Glycosidic linkages in oligosaccharides play essential roles in determining their chemical properties and biological activities. MSⁿ has been widely used to infer glycosidic linkages but requires a substantial amount of starting material, which limits its application. In addition, there is a lack of rigorous research on what MSⁿ protocols are proper for characterizing glycosidic linkages. In this work, to deliver high-quality experimental data and analysis results, we propose a machine learning-based framework to establish appropriate MSⁿ protocols and build effective data analysis methods. We demonstrate the proof-of-principle by applying our approach to elucidate sialic acid linkages (α2'-3' and α2'-6') in a set of sialyllactose stand

SUBMITTER: Ni X 

PROVIDER: S-EPMC10557947 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature