Carbohydrate NMR chemical shift prediction by GeqShift employing E(3) equivariant graph neural networks-Reference-Cited by-同舟云学术

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Carbohydrate NMR chemical shift prediction by GeqShift employing E(3) equivariant graph neural networks

Published:2024 Issue:36 Volume:14 Page:26585-26595
ISSN:2046-2069
Container-title:RSC Advances
language:en
Short-container-title:RSC Adv.

Author:

Bånkestad Maria¹²^ORCID,Dorst Kevin M.³^ORCID,Widmalm Göran³^ORCID,Rönnols Jerk²

Affiliation:

1. Department of Information Technology, Uppsala University, Sweden

2. RISE Research Institutes of Sweden, Stockholm, Sweden

3. Department of Organic Chemistry, Stockholm University, Sweden

Abstract

Visual abstract of GeqShift, an E(3) equivariant graph neural network for predicting carbohydrate NMR shifts. The model excels in stereochemical invariance, offering superior molecular geometry understanding over traditional methods.

Funder

Vetenskapsrådet

Knut och Alice Wallenbergs Stiftelse

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/RA/D4RA03428G

Reference51 articles.

1. Rapid cyclic ion mobility separations of monosaccharide building blocks as a first step toward a high-throughput reaction screening platform for carbohydrate syntheses

2. Linker, loading, and reaction scale influence automated glycan assembly

3. Complete assignments of the 1H and 13C chemical shifts and JH,H coupling constants in NMR spectra of d-glucopyranose and all d-glucopyranosyl-d-glucopyranosides

4. Primary Structure of Glycans by NMR Spectroscopy

5. Glycan Stability and Flexibility: Thermodynamic and Kinetic Characterization of Nonconventional Hydrogen Bonding in Lewis Antigens

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