A Useful Guide to Lectin Binding: Machine-Learning Directed Annotation of 57 Unique Lectin Specificities

Bojar, Daniel; Meche, Lawrence; Meng, Guanmin; Eng, William; Smith, David F.; Cummings, Richard D.; Mahal, Lara K.

doi:10.1021/acschembio.1c00689

articleACS Chemical BiologyJan 27, 2022HYBRID OA

A Useful Guide to Lectin Binding: Machine-Learning Directed Annotation of 57 Unique Lectin Specificities

DBDaniel Bojar LMLawrence Meche GMGuanmin Meng WEWilliam Eng DFDavid F. Smith

University of Gothenburg · New York University · +4 more institutions

PubMed

Indexed incrossrefpubmed

Abstract

-glycan, fucose, sialic acid and sulfate, GlcNAc and chitin, Gal and LacNAc, and GalNAc. Our work provides fresh insights into the complex binding features of commercially available lectins in current use, providing a critical guide to these important reagents.

Citation impact

374

total citations

FWCI: 28.85
Percentile: 100%
References: 141

Citations per year

Authors

DB
Daniel Bojar
University of Gothenburg
LM
Lawrence Meche
New York University
GM
Guanmin Meng
University of Alberta
WE
William Eng
New York University
DF
David F. Smith
Emory University

Topics & keywords

Topics

Glycosylation and Glycoproteins Research100%
Carbohydrate Chemistry and Synthesis100%
Galectins and Cancer Biology99%

Keywords

Glycan
Glycomics
Computational biology
Lectin
Glycobiology
Biology
Glycome
Biochemistry

No related works found for this paper.

Funding

CE
Canada Excellence Research Chairs, Government of Canada
NI
National Institute of General Medical Sciences
Awards: R24 GM137763, U54 GM062116-10, P41 GM103694
NI
National Institute of Allergy and Infectious Diseases
Award: 75N93019C00052