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

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

Журнал

Bioinformatics
ISSN: 1367-4811 , E-ISSN: 1367-4803

Вых. Данные

Год: 2017, Том: 34, Номер: 6, Страницы: 957-963 Страниц : 7 DOI: 10.1093/bioinformatics/btx696

Авторы

Kapaev Roman R ¹ , Toukach Philip V ²

Организации

1	Higher Chemical College, Russian Academy of Sciences, Moscow, Russia
2	N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Moscow, Russia

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.

Kapaev R.R. , Toukach P.V.
GRASS: semi-automated NMR-based structure elucidation of saccharides
Bioinformatics. 2017. V.34. N6. P.957-963. DOI: 10.1093/bioinformatics/btx696 WOS Scopus OpenAlex

≡ Web of science:	WOS:000427887200008
≡ Scopus:	2-s2.0-85044255704
≡ OpenAlex:	W2765346837