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Updated: May 2, 2026

Engineering Antiviral Agents via Surface Plasmon Resonance
Published on: June 14, 2022
A flexible docking scheme efficiently captures the energetics of glycan-cyanovirin binding
Ashini Bolia1, Brian W Woodrum1, Angelo Cereda1
1Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona.
Abstract:
Cyanovirin-N (CVN), a cyanobacterial lectin, exemplifies a class of antiviral agents that inhibit HIV by binding to the highly glycosylated envelope protein gp120. Here, we investigate the energetics of glycan recognition using a computationally inexpensive flexible docking approach, backbone perturbation docking (BP-Dock). We benchmarked our method using two mutants of CVN: P51G-m4-CVN, which binds dimannose with high affinity through domain B, and CVN((mutDB)), in which binding to domain B has been abolished through mutation of five polar residues to small nonpolar side chains. We investigated the energetic contribution of these polar residues along with the additional position 53 by docking dimannose to single-point CVN mutant models. Analysis of the docking simulations indicated that the E41A/G and T57A mutations led to a significant decrease in binding energy scores due to rearrangements of the hydrogen-bond network that reverberated throughout the binding cavity. N42A decreased the binding score to a level comparable to that of CVN((mutDB)) by affecting the integrity of the local protein structure. In contrast, N53S resulted in a high binding energy score, similar to P51G-m4-CVN. Experimental characterization of the five mutants by NMR spectroscopy confirmed the binding affinity pattern predicted by BP-Dock. Despite their mostly conserved fold and stability, E41A, E41G, and T57A displayed dissociation constants in the millimolar range. N53S showed a binding constant in the low micromolar range, similar to that observed for P51G-m4-CVN. No binding was observed for N42A. Our results show that BP-Dock is a useful tool for rapidly screening the relative binding affinity pattern of in silico-designed mutants compared with wild-type, supporting its use to design novel mutants with enhanced binding properties.
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