Analysis of Glycan Recognition by Concanavalin A Using\nAbsolute Binding Free Energy Calculations

Carbohydrates are\nkey biological mediators of molecular recognition\nand signaling processes. In this case study, we explore the ability\nof absolute binding free energy (ABFE) calculations to predict the\naffinities of a set of five related carbohydrate ligands for the lectin\nprotein, concanavalin A, ranging from 27-atom monosaccharides to a\n120-atom complex-type N-linked glycan core pentasaccharide. ABFE calculations\nquantitatively rank and estimate the affinity of the ligands in relation\nto microcalorimetry, with a mean signed error in the binding free\nenergy of −0.63 ± 0.04 kcal/mol. Consequently, the diminished\nbinding efficiencies of the larger carbohydrate ligands are closely\nreproduced: the ligand efficiency values from isothermal titration\ncalorimetry for the glycan core pentasaccharide and its constituent\ntrisaccharide and monosaccharide compounds are respectively −0.14,\n−0.22, and −0.41 kcal/mol per heavy atom. ABFE calculations\npredict these ligand efficiencies to be −0.14 ± 0.02,\n−0.24 ± 0.03, and −0.46 ± 0.06 kcal/mol per\nheavy atom, respectively. Consequently, the ABFE method correctly\nidentifies the high affinity of the key anchoring mannose residue\nand the negligible contribution to binding of both β-GlcNAc\narms of the pentasaccharide. While challenges remain in sampling the\nconformation and interactions of these polar, flexible, and weakly\nbound ligands, we nevertheless find that the ABFE method performs\nwell for this lectin system. The approach shows promise as a quantitative\ntool for predicting and deconvoluting carbohydrate–protein\ninteractions, with potential application to design of therapeutics,\nvaccines, and diagnostics.

Publication Details

Journal
Figshare
Published
2024-10-16
DOI
https://doi.org/10.1021/acs.jcim.4c01088.s002
Primary Topic
Mycorrhizal Fungi and Plant Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of Glycan Recognition by Concanavalin A Using\nAbsolute Binding Free Energy Calculations

Figshare
Mycorrhizal Fungi and Plant Interactions
article

Analysis of Glycan Recognition by Concanavalin A Using\nAbsolute Binding Free Energy Calculations

article en

Abstract

Carbohydrates are\nkey biological mediators of molecular recognition\nand signaling processes. In this case study, we explore the ability\nof absolute binding free energy (ABFE) calculations to predict the\naffinities of a set of five related carbohydrate ligands for the lectin\nprotein, concanavalin A, ranging from 27-atom monosaccharides to a\n120-atom complex-type N-linked glycan core pentasaccharide. ABFE calculations\nquantitatively rank and estimate the affinity of the ligands in relation\nto microcalorimetry, with a mean signed error in the binding free\nenergy of −0.63 ± 0.04 kcal/mol. Consequently, the diminished\nbinding efficiencies of the larger carbohydrate ligands are closely\nreproduced: the ligand efficiency values from isothermal titration\ncalorimetry for the glycan core pentasaccharide and its constituent\ntrisaccharide and monosaccharide compounds are respectively −0.14,\n−0.22, and −0.41 kcal/mol per heavy atom. ABFE calculations\npredict these ligand efficiencies to be −0.14 ± 0.02,\n−0.24 ± 0.03, and −0.46 ± 0.06 kcal/mol per\nheavy atom, respectively. Consequently, the ABFE method correctly\nidentifies the high affinity of the key anchoring mannose residue\nand the negligible contribution to binding of both β-GlcNAc\narms of the pentasaccharide. While challenges remain in sampling the\nconformation and interactions of these polar, flexible, and weakly\nbound ligands, we nevertheless find that the ABFE method performs\nwell for this lectin system. The approach shows promise as a quantitative\ntool for predicting and deconvoluting carbohydrate–protein\ninteractions, with potential application to design of therapeutics,\nvaccines, and diagnostics.

Figshare
Affordable and clean energy
Openalex Percentile: Top 65%
Mycorrhizal Fungi and Plant Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.