Computational models explain the oligosaccharide specificity of cyanovirin-N

A Designed "Nested" Dimer of Cyanovirin-N Increases Antiviral Activity

Cyanovirin-N (CV-N) is an antiviral lectin with potent activity against enveloped viruses, including HIV. The mechanism of action involves high affinity binding to mannose-rich glycans that decorate the surface of enveloped viruses. In the case of HIV, antiviral activity of CV-N is postulated to require multivalent interactions with envelope protein gp120, achieved through a pseudo-repeat of sequence that adopts two near-identical glycan-binding sites, and possibly involves a 3D-domain-swapped dimeric form of CV-N. Here, we present a covalent dimer of CV-N that increases the number of active glycan-binding sites, and we characterize its ability to recognize four glycans in solution. A CV-N variant was designed in which two native repeats were separated by the “nested” covalent insertion of two additional repeats of CV-N, resulting in four possible glycan-binding sites. The resulting Nested CV-N folds into a wild-type-like structure as assessed by circular dichroism and NMR spectroscopy, and displays high thermal stability with a T_m of 59 °C, identical to WT. All four glycan-binding domains encompassed by the sequence are functional as demonstrated by isothermal titration calorimetry, which revealed two sets of binding events to dimannose with dissociation constants K_d of 25 μM and 900 μM, assigned to domains B and B’ and domains A and A’ respectively. Nested CV-N displays a slight increase in activity when compared to WT CV-N in both an anti-HIV cellular assay and a fusion assay. This construct conserves the original binding specifityies of domain A and B, thus indicating correct fold of the two CV-N repeats. Thus, rational design can be used to increase multivalency in antiviral lectins in a controlled manner.

A Rigid Hinge Region Is Necessary for High-Affinity Binding of Dimannose to Cyanovirin and Associated Constructs

Mutations in the hinge region of cyanovirin-N (CVN) dictate its preferential oligomerization state. Constructs with the Pro51Gly mutation preferentially exist as monomers, whereas wild-type cyanovirin can form domain-swapped dimers under certain conditions. Because the hinge region is an integral part of the high-affinity binding site of CVN, we investigated whether this mutation affects the shape, flexibility, and binding affinity of domain B for dimannose. Our studies indicate that the capability of monomeric wild-type CVN to resist mechanical perturbations is enhanced when compared to that of constructs in which the hinge region is more flexible. Our computational results also show that enhanced flexibility leads to blocking of the binding site by allowing different rotational isomeric states of Asn53. Moreover, at higher temperatures, this observed flexibility leads to an interaction between Asn53 and Asn42, further hindering access to the binding site. On the basis of these results, we predicted that binding affinity for dimannose would be more favorable for cyanovirin constructs containing a wild-type hinge region, whereas affinity would be impaired in the case of mutants containing Pro51Gly. Experimental characterization by isothermal titration calorimetry of a set of cyanovirin mutants confirms this hypothesis. Those possessing the Pro51Gly mutation are consistently inferior binders.

Recent developments in therapeutic applications of Cyanobacteria

The cyanobacteria (blue-green algae) are photosynthetic prokaryotes having applications in human health with numerous biological activities and as a dietary supplement. It is used as a food supplement because of its richness in nutrients and digestibility. Many cyanobacteria (Microcystis sp, Anabaena sp, Nostoc sp, Oscillatoria sp., etc.) produce a great variety of secondary metabolites with potent biological activities. Cyanobacteria produce biologically active and chemically diverse compounds belonging to cyclic peptides, lipopeptides, fatty acid amides, alkaloids and saccharides. More than 50% of the marine cyanobacteria are potentially exploitable for extracting bioactive substances which are effective in killing cancer cells by inducing apoptotic death. Their role as anti-viral, anti-tumor, antimicrobial, anti-HIV and a food additive have also been well established. However, such products are at different stages of clinical trials and only a few compounds have reached to the market.

A flexible docking scheme efficiently captures the energetics of glycan-cyanovirin binding

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.

The antiviral lectin cyanovirin-N: probing multivalency and glycan recognition through experimental and computational approaches

CVN (cyanovirin-N), a small lectin isolated from cyanobacteria, exemplifies a novel class of anti-HIV agents that act by binding to the highly glycosylated envelope protein gp120 (glycoprotein 120), resulting in inhibition of the crucial viral entry step. In the present review, we summarize recent work in our laboratory and others towards determining the crucial role of multivalency in the antiviral activity, and we discuss features that contribute to the high specificity and affinity for the glycan ligand observed in CVN. An integrated approach that encompasses structural determination, mutagenesis analysis and computational work holds particular promise to clarify aspects of the interactions between CVN and glycans.

The role of Glu41 in the binding of dimannose to P51G-m4-CVN

The carbohydrate binding protein, Cyanovirin-N, obtained from cyanobacteria, consists of high-affinity and low-affinity binding domains. To avoid the formation of a domain swapped structure in solution and also to better focus on the binding of carbohydrates at the high-affinity site, the Ghirlanda group (Biochemistry, 46, 2007, 9199-9207) engineered the P51G-m4-CVN mutant which does not dimerize nor binds at the low-affinity site. This mutant provides an excellent starting point for the experimental and computational study of further transformations to enhance binding at the high-affinity site as well as to retool this site for the possible binding of different sugars. However, before such endeavors are pursued, detailed understanding of apparently key interactions both present in wild-type and P51G-m4-CVN at the high-affinity site must be derived and controversies about the importance of certain residues must be resolved. One such interaction is that of Glu41, a charged residue in intimate contact with 2'OH of dimannose at the nonreducing end. We do so computationally by performing two mutations using the thermodynamic integration formalism in explicit solvent. Mutations of P51G-m4-CVN Glu41 to Ala41 and Gly41 reveal that whereas the loss of Coulomb interactions result in a free energy penalty of about 2.1 kcal/mol, this is significantly compensated by favorable contributions to the Lennard-Jones portion of the transformation, resulting in almost no change in the free energy of binding. At least in terms of free energetics, and in the case of this particular CVN mutant, Glu41 does not appear to be as important as previously thought. This is not because of lack of extensive hydrogen bonding with the ligand but instead because of other compensating factors.

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.

Rational and computational design of stabilized variants of cyanovirin-N that retain affinity and specificity for glycan ligands

Cyanovirin-N (CVN) is an 11 kDa pseudosymmetric cyanobacterial lectin that has been shown to inhibit infection by the human immunodeficiency virus by binding to high-mannose oligosaccharides on the surface of the viral envelope glycoprotein gp120. In this work, we describe rationally designed CVN variants that stabilize the protein fold while maintaining high affinity and selectivity for their glycan targets. Poisson-Boltzmann calculations and protein repacking algorithms were used to select stabilizing mutations in the protein core. By substituting the buried polar side chains of Ser11, Ser20, and Thr61 with aliphatic groups, we stabilized CVN by nearly 12 °C against thermal denaturation, and by 1 M GuaHCl against chemical denaturation, relative to a previously characterized stabilized mutant. Glycan microarray binding experiments confirmed that the specificity profile of carbohydrate binding is unperturbed by the mutations and is identical for all variants. In particular, the variants selectively bound glycans containing the Manα(1→2)Man linkage, which is the known minimal binding unit of CVN. We also report the slow denaturation kinetics of CVN and show that they can complicate thermodynamic analysis; in particular, the unfolding of CVN cannot be described as a fixed two-state transition. Accurate thermodynamic parameters are needed to describe the complicated free energy landscape of CVN, and we provide updated values for CVN unfolding.

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein-carbohydrate interaction are reviewed.

Energetic decomposition with the generalized-born and Poisson-Boltzmann solvent models: lessons from association of G-protein components

Continuum electrostatic models have been shown to be powerful tools in providing insight into the energetics of biomolecular processes. While the Poisson-Boltzmann (PB) equation provides a theoretically rigorous approach to computing electrostatic free energies of solution in such a model, computational cost makes its use for large ensembles of states impractical. The generalized-Born (GB) approximation provides a much faster alternative, although with a weaker theoretical framework. While much attention has been given to how GB recapitulates PB energetics for the overall stability of a biomolecule or the affinity of a complex, little attention has been given to how the contributions of individual functional groups are captured by the two methods. Accurately capturing these individual electrostatic components is essential both for the development of a mechanistic understanding of biomolecular processes and for the design of variant sequences and structures with desired properties. Here, we present a detailed comparison of the group-wise decomposition of both PB and GB electrostatic free energies of binding, using association of various components of the heterotrimeric-G-protein complex as a model. We find that, while net binding free energies are strongly correlated in the two models, the correlations of individual group contributions are highly variable; in some cases, strong correlation is seen, while in others, there is essentially none. Structurally, the GB model seems to capture the magnitude of direct, short-range electrostatic interactions quite well but performs more poorly with moderate-range "action-at-a-distance" interactions--GB has a tendency to overestimate solvent screening over moderate distances, and to underestimate the costs of desolvating charged groups somewhat removed from the binding interface. Despite this, however, GB does seem to be quite effective as a predictor of those groups that will be computed to be most significant in a PB-based model.

Solution and crystal molecular dynamics simulation study of m4-cyanovirin-N mutants complexed with di-mannose

Cyanovirin-N (CVN) is a highly potent anti-HIV carbohydrate-binding agent that establishes its microbicide activity through interaction with mannose-rich glycoprotein gp120 on the virion surface. The m4-CVN and P51G-m4-CVN mutants represent simple models for studying the high-affinity binding site, B(M). A recently determined 1.35 A high-resolution structure of P51G-m4-CVN provided details on the di-mannose binding mechanism, and suggested that the Arg-76 and Glu-41 residues are critical components of high mannose specificity and affinity. We performed molecular-dynamics simulations in solution and a crystal environment to study the role of Arg-76. Network analysis and clustering were used to characterize the dynamics of Arg-76. The results of our explicit solvent solution and crystal simulations showed a significant correlation with conformations of Arg-76 proposed from x-ray crystallographic studies. However, the crystal simulation showed that the crystal environment strongly biases conformational sampling of the Arg-76 residue. The solution simulations demonstrated no conformational preferences for Arg-76, which would support its critical role as the residue that locks the ligand in the bound state. Instead, a comparative analysis of trajectories from >50 ns of simulation for two mutants revealed the existence of a very stable eight-hydrogen-bond network between the di-mannose ligand and predominantly main-chain atoms. This network may play a key role in the specific recognition and strong binding of mannose oligomers in CVN and its homologs.

Structure, dynamics, and interactions of jacalin. Insights from molecular dynamics simulations examined in conjunction with results of X-ray studies

Molecular dynamics simulations have been carried out on all the jacalin-carbohydrate complexes of known structure, models of unliganded molecules derived from the complexes and also models of relevant complexes where X-ray structures are not available. Results of the simulations and the available crystal structures involving jacalin permit delineation of the relatively rigid and flexible regions of the molecule and the dynamical variability of the hydrogen bonds involved in stabilizing the structure. Local flexibility appears to be related to solvent accessibility. Hydrogen bonds involving side chains and water bridges involving buried water molecules appear to be important in the stabilization of loop structures. The lectin-carbohydrate interactions observed in crystal structures, the average parameters pertaining to them derived from simulations, energetic contribution of the stacking residue estimated from quantum mechanical calculations, and the scatter of the locations of carbohydrate and carbohydrate-binding residues are consistent with the known thermodynamic parameters of jacalin-carbohydrate interactions. The simulations, along with X-ray results, provide a fuller picture of carbohydrate binding by jacalin than provided by crystallographic analysis alone. The simulations confirm that in the unliganded structures water molecules tend to occupy the positions occupied by carbohydrate oxygens in the lectin-carbohydrate complexes. Population distributions in simulations of the free lectin, the ligands, and the complexes indicate a combination of conformational selection and induced fit.

PLecDom: a program for identification and analysis of plant lectin domains

PLecDom is a program for detection of Plant Lectin Domains in a polypeptide or EST sequence, followed by a classification of the identified domains into known families. The web server is a collection of plant lectin domain families represented by alignments and profile Hidden Markov Models. PLecDom was developed after a rigorous analysis of evolutionary relationships between available sequences of lectin domains with known specificities. Users can test their sequences for potential lectin domains, catalog the identified domains into broad substrate classes, estimate the extent of divergence of new domains with existing homologs, extract domain boundaries and examine flanking sequences for further analysis. The high prediction accuracy of PLecDom combined with the ease with which it handles large scale input, enabled us to apply the program to protein and EST data from 48 plant genome-sequencing projects in various stages of completion. Our results represent a significant enrichment of the currently annotated plant lectins, and highlight potential targets for biochemical characterization. The search algorithm requires input in fasta format and is designed to process simultaneous connection requests from multiple users, such that huge sets of input sequences can be scanned in a matter of seconds. PLecDom is available at http://www.nipgr.res.in/plecdom.html.