GRASS: semi-automated NMR-based structure elucidation of saccharides

• Published in: Bioinformatics Vol. 34; no. 6; pp. 957 - 963
• Main Authors: Kapaev, Roman R, Toukach, Philip V
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 15.03.2018
• Subjects: Animals; Bacteria - metabolism; Carbohydrate Conformation; Computational Biology - methods; Glycomics - methods; Humans; Internet; Magnetic Resonance Spectroscopy - methods; Software
• ISSN: 1367-4803; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btx696

Abstract Motivation Carbohydrates play crucial roles in various biochemical processes and are useful for developing drugs and vaccines. However, in case of carbohydrates, the primary structure elucidation is usually a sophisticated task. Therefore, they remain the least structurally characterized class of biomolecules, and it hampers the progress in glycochemistry and glycobiology. Creating a usable instrument designed to assist researchers in natural carbohydrate structure determination would advance glycochemistry in biomedical and pharmaceutical applications. Results We present GRASS (Generation, Ranking and Assignment of Saccharide Structures), a novel method for semi-automated elucidation of carbohydrate and derivative structures which uses unassigned 13C NMR spectra and information obtained from chromatography, optical, chemical and other methods. This approach is based on new methods of carbohydrate NMR simulation recently reported as the most accurate. It combines a broad diversity of supported structural features, high accuracy and performance. Availability and implementation GRASS is implemented in a free web tool available at http://csdb.glycoscience.ru/grass.html. Supplementary information Supplementary data are available at Bioinformatics online.