Carbohydrate recognition by the antiviral lectin cyanovirin-N.

Cyanovirin-N (CVN) is a cyanobacterial lectin with potent antiviral activity and has been the focus of extensive preclinical investigation as a potential prophylactic for the prevention of the sexual transmission of the human immunodeficiency virus (HIV). Here we present a detailed analysis of carbohydrate recognition by this important protein, using a combination of computational methods, including extensive molecular dynamics simulations and molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) energetic analysis. The simulation results strongly suggest that the observed tendency of wild-type CVN to form domain-swapped dimers is the result of a previously unidentified cis-peptide bond present in the monomeric state. The energetic analysis additionally indicates that the highest-affinity ligand for CVN characterized to date (α-Man-(1,2)-α-Man-(1,2)-α-Man) is recognized asymmetrically by the two binding sites. Finally, we are able to provide a detailed map of the role of all binding site functional groups (both backbone and side chain) to various aspects of molecular recognition: general affinity for cognate ligands, specificity for distinct oligosaccharide targets, and the asymmetric recognition of α-Man-(1,2)-α-Man-(1,2)-α-Man. Taken as a whole, these results complement past experimental characterization (both structural and thermodynamic) to provide the most complete understanding of carbohydrate recognition by CVN to date. The results also provide strong support for the application of similar approaches to the understanding of other protein-carbohydrate complexes.

Computational models explain the oligosaccharide specificity of cyanovirin-N.

The prokaryotic lectin cyanovirin-N (CV-N) is a potent inhibitor of HIV envelope-mediated cell entry, and thus is a leading candidate among a new class of potential anti-HIV microbicides. The activity of CV-N is a result of interactions with the D1 arm of high-mannose oligosaccharides on the viral glycoprotein gp120. Here, we present computationally refined models of CV-N recognition of the di- and trisaccharides that represent the terminal three sugars of the D1 arm by each CV-N binding site. These models complement existing structural data, both from NMR spectroscopy and X-ray crystallography. When used with a molecular dynamics/continuum electrostatic (MD/PBSA) approach to compute binding free energies, these models explain the relative affinity of each site for the two saccharides. This work presents the first validation of the application of continuum electrostatic models to carbohydrate-protein association. Taken as a whole, the results both provide models of CV-N sugar recognition and demonstrate the utility of these computational methods for the study of carbohydrate-binding proteins.