Theoretical studies on the conformation of β-D-N-acetyl neuraminic acid (sialic acid)

The possible conformations of sialic acid were analysed using semi-empirical potential functions. The solid state conformation has approx. 0.2 kcal/mol higher energy than the minimum energy conformation. These studies suggest that in solution sialic acid may exist preponderantly in two different conformations which differ in the orientation of the terminal hydroxymethyl group of glycerol side-chain. The present model is consistent with ¹H- and ¹³C-NMR data, but differs from the earlier models.     

Conformations of Higher Gangliosides and Their Binding with Cholera Toxin—Investigation by Molecular Modeling,Molecular Mechanics,and Molecular Dynamics

Abstract

Molecular mechanics and molecular dynamics studies are performed to investigate the conformational preference of cell surface higher gangliosides (GT1A and GT1B) and their interaction with Cholera Toxin. The water mediated hydrogen bonding network exists between sugar residues in gangliosides. An integrated molecular modeling, molecular mechanics, and molecular dynamics calculation of cholera toxin complexed with GT1A and GT1B reveal that, the active site of cholera toxin can accommodate these higher gangliosides. Direct and water mediated hydrogen bonding interactions stabilize these binding modes and play an essential role in defining the order of specificity for different higher ganglioside towards cholera toxin. This study identifies that the binding site of cholera toxin is shallow and can accommodate a maximum of two NeuNAc residues. The NeuNAc binding site of cholera toxin may be crucial for the design of inhibitors that can prevent the infection of cholera.     

Theoretical investigation on the glycan‐binding specificity of Agrocybe cylindracea galectin using molecular modeling and molecular dynamics simulation studies

Galectins are β‐galactoside binding proteins which have the ability to serve as potent antitumor, cancer biomarker, and induce tumor cell apoptosis. Agrocybe cylindracea galectin (ACG) is a fungal galectin which specifically recognizes α(2,3)‐linked sialyllactose at the cell surface that plays extensive roles in the biological recognition processes. To investigate the change in glycan‐binding specificity upon mutations, single point and double point site‐directed in silico mutations are performed at the binding pocket of ACG. Molecular dynamics (MD) simulation studies are carried out for the wild‐type (ACG) and single point (ACG1) and double point (ACG2) mutated ACGs to investigate the dynamics of substituted mutants and their interactions with the receptor sialyllactose. Plausible binding modes are proposed for galectin–sialylglycan complexes based on the analysis of hydrogen bonding interactions, total pair‐wise interaction energy between the interacting binding site residues and sialyllactose and binding free energy of the complexes using molecular mechanics–Poisson–Boltzmann surface area. Our result shows that high contribution to the binding in different modes is due to the direct and water‐mediated hydrogen bonds. The binding specificity of double point mutant Y59R/N140Q of ACG2 is found to be high, and it has 26 direct and water‐mediated hydrogen bonds with a relatively low‐binding free energy of −47.52 ± 5.2 kcal/mol. We also observe that the substituted mutant Arg59 is crucial for glycan‐binding and for the preference of α(2,3)‐linked sialyllactose at the binding pocket of ACG2 galectin. When compared with the wild‐type and single point mutant, the double point mutant exhibits enhanced affinity towards α(2,3)‐linked sialyllactose, which can be effectively used as a model for biological cell marker in cancer therapeutics. Copyright © 2015 John Wiley & Sons, Ltd.     

Insights into the binding specificity of wild type and mutated wheat germ agglutinin towards Neu5Acα(2‐3)Gal: a study by in silico mutations and molecular dynamics simulations

Wheat germ agglutinin (WGA) is a plant lectin, which specifically recognizes the sugars NeuNAc and GlcNAc. Mutated WGA with enhanced binding specificity can be used as biomarkers for cancer. In silico mutations are performed at the active site of WGA to enhance the binding specificity towards sialylglycans, and molecular dynamics simulations of 20 ns are carried out for wild type and mutated WGAs (WGA1, WGA2, and WGA3) in complex with sialylgalactose to examine the change in binding specificity. MD simulations reveal the change in binding specificity of wild type and mutated WGAs towards sialylgalactose and bound conformational flexibility of sialylgalactose. The mutated polar amino acid residues Asn114 (S114N), Lys118 (G118K), and Arg118 (G118R) make direct and water mediated hydrogen bonds and hydrophobic interactions with sialylgalactose. An analysis of possible hydrogen bonds, hydrophobic interactions, total pair wise interaction energy between active site residues and sialylgalactose and MM‐PBSA free energy calculation reveals the plausible binding modes and the role of water in stabilizing different binding modes. An interesting observation is that the binding specificity of mutated WGAs (cyborg lectin) towards sialylgalactose is found to be higher in double point mutation (WGA3). One of the substituted residues Arg118 plays a crucial role in sugar binding. Based on the interactions and energy calculations, it is concluded that the order of binding specificity of WGAs towards sialylgalactose is WGA3 > WGA1 > WGA2 > WGA. On comparing with the wild type, double point mutated WGA (WGA3) exhibits increased specificity towards sialylgalactose, and thus, it can be effectively used in targeted drug delivery and as biological cell marker in cancer therapeutics. Copyright © 2014 John Wiley & Sons, Ltd.     

Database analysis of O-glycosylation sites in proteins

Statistical analysis was carried out to study the sequential aspects of amino acids around the O-glycosylated Ser/Thr. 992 sequences containing O-glycosylated Ser/Thr were selected from the O-GLYCBASE database of O-glycosylated proteins. The frequency of occurrence of amino acid residues around the glycosylated Ser/Thr revealed that there is an increased number of proline residues around the O-glycosylation sites in comparison with the nonglycosylated serine and threonine residues. The deviation parameter calculated as a measure of preferential and nonpreferential occurrence of amino acid residues around the glycosylation site shows that Pro has the maximum preference around the O-glycosylation site. Pro at +3 and/or -1 positions strongly favors glycosylation irrespective of single and multiple glycosylation sites. In addition, serine and threonine are preferred around the multiple glycosylation sites due to the effect of clusters of closely spaced glycosylated Ser/Thr. The preference of amino acids around the sites of mucin-type glycosylation is found likely to be similar to that of the O-glycosylation sites when taken together, but the acidic amino acids are more preferred around Ser/Thr in mucin-type glycosylation when compared totally. Aromatic amino acids hinder O-glycosylation in contrast to N-glycosylation. Cysteine and amino acids with bulky side chains inhibit O-glycosylation. The preference of certain potential sequence motifs of glycosylation has been discussed.     

Generation of deviation parameters for amino acid singlets, doublets and triplets from three-dimensional structures of proteins and its implications for secondary structure prediction from amino acid sequences

We present a new method, secondary structure prediction by deviation parameter (SSPDP) for predicting the secondary structure of proteins from amino acid sequence. Deviation parameters (DP) for amino acid singlets, doublets and triplets were computed with respect to secondary structural elements of proteins based on the dictionary of secondary structure prediction (DSSP)-generated secondary structure for 408 selected nonhomologous proteins. To the amino acid triplets which are not found in the selected dataset, a DP value of zero is assigned with respect to the secondary structural elements of proteins. The total number of parameters generated is 15,432, in the possible parameters of 25,260. Deviation parameter is complete with respect to amino acid singlets, doublets, and partially complete with respect to amino acid triplets. These generated parameters were used to predict secondary structural elements from amino acid sequence. The secondary structure predicted by our method (SSPDP) was compared with that of single sequence (NNPREDICT) and multiple sequence (PHD) methods. The average value of the percentage of prediction accuracy for αhelix by SSPDP, NNPREDICT and PHD methods was found to be 57%, 44% and 69% respectively for the proteins in the selected dataset. For Β-strand the prediction accuracy is found to be 69%, 21% and 53% respectively by SSPDP, NNPREDICT and PHD methods. This clearly indicates that the secondary structure prediction by our method is as good as PHD method but much better than NNPREDICT method.     

Studies on the conformations of sialyloligosaccharides and implications

Theoretical investigations, using semi-empirical potential functions have been carried out to predict the favoured conformations of the terminal dissaccharide fragments of various sialyloligosaccharides. The proposed conformational similarity for these fragments has been correlated to the binding specificity of neuraminidases. These calculations predict that bacterial neuraminidases have a binding site which can accommodate only two sugar residues and virus neuraminidases have a binding site which can accommodate more than two sugar residues.     

Conformational dynamics of sialyl Lewisx in aqueous solution and its interaction with selectinE. A study by molecular dynamics

Three dimensional structures of sialyl Lewis(x) (SLe(x)) in aqueous solution and bound to selectinE are described based on an exhaustive conformational analysis and several long molecular dynamics simulations using different glycosidic regions as starting conformations. It appears from this study that when the oligosaccharide is free in solution the NeuNAcalpha(2-3)Gal segment favors glycosidic conformation in three different regions in the (Phi,Psi) plane with propensity of populations in the ratio 1:8:1. Each one of these structures is characteristically stabilized by specific hydrogen bonding interaction between NeuNAc and Gal. On the other hand, the Gal-GlcNAc-Fuc segment can exist in four different conformational states. Based on the topology of SLe(x) we are able to predict that out of all the allowed conformations in solution only two of these structures possess a geometry that would fit without steric clashes into the binding location of selectinE. In both of these binding modes, segment Gal-GlcNAc-Fuc adopts a unique conformation. The only difference between the two SLe(x) conformers that can successfully bind to selectinE is given by two possible regions in glycosidic space in the fragment NeuNAcalpha(2-3)Gal. A large conformational departure from the crystallographic data is observed for two lysine residues at the binding site of selectinE. These two residues play an important role when SLe(x) binds selectinE in aqueous solution. These findings help reconcile the X-ray data, in which these residues appear to be 1 nm away from SLe(x), with recent liquid NMR data reporting couplings between these protein residues and the sugar.     

3DSDSCAR—a three dimensional structural database for sialic acid-containing carbohydrates through molecular dynamics simulation

The inherent flexibility and lack of strong intramolecular interactions of oligosaccharides demand the use of theoretical methods for their structural elucidation. In spite of the developments of theoretical methods, not much research on glycoinformatics is done so far when compared to bioinformatics research on proteins and nucleic acids. We have developed three dimensional structural database for a sialic acid-containing carbohydrates (3DSDSCAR). This is an open-access database that provides 3D structural models of a given sialic acid-containing carbohydrate. At present, 3DSDSCAR contains 60 conformational models, belonging to 14 different sialic acid-containing carbohydrates, deduced through 10 ns molecular dynamics (MD) simulations. The database is available at the URL: http://www.3dsdscar.org.     

Theoretical Investigation on the Binding Specificity of Sialyldisaccharides with Hemagglutinins of Influenza A Virus by Molecular Dynamics Simulations

Recognition of cell-surface sialyldisaccharides by influenza A hemagglutinin (HA) triggers the infection process of influenza. The changes in glycosidic torsional linkage and the receptor conformations may alter the binding specificity of HAs to the sialylglycans. In this study, 10-ns molecular dynamics simulations were carried out to examine the structural and dynamic behavior of the HAs bound with sialyldisaccharides Neu5Acα(2–3)Gal (N23G) and Neu5Acα(2–6)Gal (N26G). The analysis of the glycosidic torsional angles and the pair interaction energy between the receptor and the interacting residues of the binding site reveal that N23G has two binding modes for H1 and H5 and a single binding mode for H3 and H9. For N26G, H1 and H3 has two binding modes, and H5 and H9 has a single binding mode. The direct and water-mediated hydrogen bonding interactions between the receptors and HAs play dominant roles in the structural stabilization of the complexes. It is concluded from pair interaction energy and Molecular Mechanic-Poisson-Boltzmann Surface Area calculations that N26G is a better receptor for H1 when compared with N23G. N23G is a better receptor for H5 when compared with N26G. However, H3 and H9 can recognize N23G and N26G in equal binding specificity due to the marginal energy difference (≈2.5 kcal/mol). The order of binding specificity of N23G is H3 > H5 > H9 > H1 and N26G is H1 > H3 > H5 > H9, respectively. The proposed conformational models will be helpful in designing inhibitors for influenza virus.