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

Carbohydrates are key biological mediators of molecular recognition and signaling processes. In this case study, we explore the ability of absolute binding free energy (ABFE) calculations to predict the affinities of a set of five related carbohydrate ligands for the lectin protein, concanavalin A, ranging from 27-atom monosaccharides to a 120-atom complex-type N-linked glycan core pentasaccharide. ABFE calculations quantitatively rank and estimate the affinity of the ligands in relation to microcalorimetry, with a mean signed error in the binding free energy of -0.63 ± 0.04 kcal/mol. Consequently, the diminished binding efficiencies of the larger carbohydrate ligands are closely reproduced: the ligand efficiency values from isothermal titration calorimetry for the glycan core pentasaccharide and its constituent trisaccharide and monosaccharide compounds are respectively -0.14, -0.22, and -0.41 kcal/mol per heavy atom. ABFE calculations predict these ligand efficiencies to be -0.14 ± 0.02, -0.24 ± 0.03, and -0.46 ± 0.06 kcal/mol per heavy atom, respectively. Consequently, the ABFE method correctly identifies the high affinity of the key anchoring mannose residue and the negligible contribution to binding of both β-GlcNAc arms of the pentasaccharide. While challenges remain in sampling the conformation and interactions of these polar, flexible, and weakly bound ligands, we nevertheless find that the ABFE method performs well for this lectin system. The approach shows promise as a quantitative tool for predicting and deconvoluting carbohydrate-protein interactions, with potential application to design of therapeutics, vaccines, and diagnostics.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2024-10-16
DOI
https://doi.org/10.1021/acs.jcim.4c01088
Citations
3
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
0.70

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article

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

Sondos Musleh, Irfan Alibay, Philip Charles Biggin, Richard A. Bryce
3 citations
Journal of Chemical Information and Modeling
Protein Structure and Dynamics
0.70
article

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

Sondos Musleh, Irfan Alibay, Philip Charles Biggin, Richard A. Bryce
article en
3 citations

Abstract

Carbohydrates are key biological mediators of molecular recognition and signaling processes. In this case study, we explore the ability of absolute binding free energy (ABFE) calculations to predict the affinities of a set of five related carbohydrate ligands for the lectin protein, concanavalin A, ranging from 27-atom monosaccharides to a 120-atom complex-type N-linked glycan core pentasaccharide. ABFE calculations quantitatively rank and estimate the affinity of the ligands in relation to microcalorimetry, with a mean signed error in the binding free energy of -0.63 ± 0.04 kcal/mol. Consequently, the diminished binding efficiencies of the larger carbohydrate ligands are closely reproduced: the ligand efficiency values from isothermal titration calorimetry for the glycan core pentasaccharide and its constituent trisaccharide and monosaccharide compounds are respectively -0.14, -0.22, and -0.41 kcal/mol per heavy atom. ABFE calculations predict these ligand efficiencies to be -0.14 ± 0.02, -0.24 ± 0.03, and -0.46 ± 0.06 kcal/mol per heavy atom, respectively. Consequently, the ABFE method correctly identifies the high affinity of the key anchoring mannose residue and the negligible contribution to binding of both β-GlcNAc arms of the pentasaccharide. While challenges remain in sampling the conformation and interactions of these polar, flexible, and weakly bound ligands, we nevertheless find that the ABFE method performs well for this lectin system. The approach shows promise as a quantitative tool for predicting and deconvoluting carbohydrate-protein interactions, with potential application to design of therapeutics, vaccines, and diagnostics.

Journal of Chemical Information and ModelingVol. 64(20)
Jordan University of Science and Technology (JO), University of Manchester (GB), University of Oxford (GB), Open Geospatial Consortium (US), Open Molecular Software Foundation, Manchester University (US)
Jordan University of Science and Technology, Engineering and Physical Sciences Research Council
Affordable and clean energy
Openalex Percentile: Top 29%
Protein Structure and Dynamics
0.70
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