Comparison of docking methods for carbohydrate binding in calcium-dependent lectins and prediction of the carbohydrate binding mode to sea cucumber lectin CEL-III

Production, homology modeling and mutagenesis studies on GlcH glucose transporter from Prochlorococcus sp. strain SS120

The marine cyanobacterium Prochlorococcus is one of the main primary producers on Earth, which can take up glucose by using the high affinity, multiphasic transporter GlcH. We report here the overexpression of glcH from Prochlorococcus marinus strain SS120 in Escherichia coli. Modeling studies of GlcH using the homologous MelB melibiose transporter from Salmonella enterica serovar Typhimurium showed high conservation at the overall fold. We observed that an important structural interaction, mediated by a strong hydrogen bond between D8 and R141, is conserved in Prochlorococcus, although the corresponding amino acids in MelB from Salmonella are different. Biased docking studies suggested that when glucose reaches the pocket of the transporter and interacts with D8 and R141, the hydrogen bond network in which these residues are involved could be disrupted, favoring a conformational change with the subsequent translocation of the glucose molecule towards the cytoplasmic region of the pmGlcH structure. Based on these theoretical predictions and on the conservation of N117 and W348 in other MelB structures, D8, N117, R141 and W348 were mutated to glycine residues. Their key role in glucose transport was evaluated by glucose uptake assays. N117G and W348G mutations led to 17 % decrease in glucose uptake, while D8G and R141G decreased the glucose transport by 66 % and 92 % respectively. Overall, our studies provide insights into the Prochlorococcus 3D-structure of GlcH, paving the way for further analysis to understand the features which are involved in the high affinity and multiphasic kinetics of this transporter.

Development and Evaluation of GlycanDock: A Protein-Glycoligand Docking Refinement Algorithm in Rosetta

Carbohydrate chains are ubiquitous in the complex molecular processes of life. These highly diverse chains are recognized by a variety of protein receptors, enabling glycans to regulate many biological functions. High-resolution structures of protein-glycoligand complexes reveal the atomic details necessary to understand this level of molecular recognition and inform application-focused scientific and engineering pursuits. When experimental challenges hinder high-throughput determination of quality structures, computational tools can, in principle, fill the gap. In this work, we introduce GlycanDock, a residue-centric protein-glycoligand docking refinement algorithm developed within the Rosetta macromolecular modeling and design software suite. We performed a benchmark docking assessment using a set of 109 experimentally determined protein-glycoligand complexes as well as 62 unbound protein structures. The GlycanDock algorithm can sample and discriminate among protein-glycoligand models of native-like structural accuracy with statistical reliability from starting structures of up to 7 Å root-mean-square deviation in the glycoligand ring atoms. We show that GlycanDock-refined models qualitatively replicated the known binding specificity of a bacterial carbohydrate-binding module. Finally, we present a protein-glycoligand docking pipeline for generating putative protein-glycoligand complexes when only the glycoligand sequence and unbound protein structure are known. In combination with other carbohydrate modeling tools, the GlycanDock docking refinement algorithm will accelerate research in the glycosciences.

Screening coronavirus and human proteins for sialic acid binding sites using a docking approach

<abstract> <p>The initial step of interaction of some pathogens with the host is driven by the interaction of glycoproteins of either side <italic>via</italic> endcaps of their glycans. These end caps consist of sialic acids or sugar molecules. Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are found to use this route of interaction. The strength and spatial interactions on the single molecule level of sialic acids with either the spike (S) protein of SARS coronaviruses, or human angiotensin-converting enzyme 2 (ACE2) and furin are probed and compared to the binding modes of those sugar molecules which are present in glycans of glycoproteins. The protocol of using single molecules is seen as a simplified but effective mimic of the complex mode of interaction of the glycans. Averaged estimated binding energies from a docking approach result in preferential binding of the sialic acids to a specific binding site of the S protein of human coronavirus OC43 (HCoV-OC43). Furin is proposed to provide better binding sites for sialic acids than ACE2, albeit outweighed by sites for other sugar molecules. Absolute minimal estimated binding energies indicate weak binding affinities and are indifferent to the type of sugar molecules and the proteins. Neither the proposed best binding sites of the sialic acids nor those of the sugar molecules overlap with any of the cleavage sites at the S protein and the active sites of the human proteins.</p> </abstract>

Discovery of selective farnesoid X receptor agonists for the treatment of hyperlipidemia from traditional Chinese medicine based on virtual screening and in vitro validation

Farnesoid X receptor (FXR), a bile acid receptor, has important roles in maintaining bile acid and cholesterol homeostasis, which is an attractive target for hyperlipidemia. Present study aimed to discover potential selective FXR agonists over G-protein coupled bile acid receptor 1 (GPBAR1, TGR5) from traditional Chinese medicine (TCM) by using virtual screening, in vitro studies and molecular dynamics simulation (MD). Ligand-based pharmacophore model for FXR was firstly built to screen FXR agonists from the Traditional Chinese Medicine Database (TCMD). Then, 21 FXR crystal structures were clustered in two types and two representative structures (PDB ID: 3OMM and 3P89) were, respectively, used to carry out molecular docking to refine the screened result. Moreover, the pharmacophore model for GPBAR1 was built to screen selective FXR agonists with no activity on GPBAR1. A set of 24 candidate selective FXR agonists which fitvalue of FXR pharmacophore model and docking score of 3OMM and 3P89 were in the top 100 and cannot match the pharmacophore model for GPBAR1 were obtained. By the lipid-lowering activity test in HepG2 cell lines, Arctigenin was identified to be potential selective FXR agonist with the activity of 20 μmol·L^-1. After down-regulating FXR, Arctigenin could increase the mRNA of FXR while exerted no effect on the mRNA of GPBAR1. MD was further used to interpret the mechanism of Arctigenin with the representative structures. This research provided a new screening procedure for finding selective candidate compounds and appropriate docking models of a target by considering the structure diversity of PDB structures, which was applied to discovery novel selective FXR agonists to treat hyperlipidemia.Communicated by Ramaswamy H. Sarma.

Predicting the Structures of Glycans, Glycoproteins, and Their Complexes

Complex carbohydrates are ubiquitous in nature, and together with proteins and nucleic acids they comprise the building blocks of life. But unlike proteins and nucleic acids, carbohydrates form nonlinear polymers, and they are not characterized by robust secondary or tertiary structures but rather by distributions of well-defined conformational states. Their molecular flexibility means that oligosaccharides are often refractory to crystallization, and nuclear magnetic resonance (NMR) spectroscopy augmented by molecular dynamics (MD) simulation is the leading method for their characterization in solution. The biological importance of carbohydrate-protein interactions, in organismal development as well as in disease, places urgency on the creation of innovative experimental and theoretical methods that can predict the specificity of such interactions and quantify their strengths. Additionally, the emerging realization that protein glycosylation impacts protein function and immunogenicity places the ability to define the mechanisms by which glycosylation impacts these features at the forefront of carbohydrate modeling. This review will discuss the relevant theoretical approaches to studying the three-dimensional structures of this fascinating class of molecules and interactions, with reference to the relevant experimental data and techniques that are key for validation of the theoretical predictions.

Computational analysis of interactions in structurally available protein-glycosaminoglycan complexes

Glycosaminoglycans represent a class of linear anionic periodic polysaccharides, which play a key role in a variety of biological processes in the extracellular matrix via interactions with their protein targets. Computationally, glycosaminoglycans are very challenging due to their high flexibility, periodicity and electrostatics-driven nature of the interactions with their protein counterparts. In this work, we carry out a detailed computational characterization of the interactions in protein-glycosaminoglycan complexes from the Protein Data Bank (PDB), which are split into two subsets accounting for their intrinsic nature: non-enzymatic-protein-glycosaminoglycan and enzyme-glycosaminoglycan complexes. We apply molecular dynamics to analyze the differences in these two subsets in terms of flexibility, retainment of the native interactions in the simulations, free energy components of binding and contributions of protein residue types to glycosaminoglycan binding. Furthermore, we systematically demonstrate that protein electrostatic potential calculations, previously found to be successful for glycosaminoglycan binding sites prediction for individual systems, are in general very useful for proposing protein surface regions as putative glycosaminoglycan binding sites, which can be further used for local docking calculations with these particular polysaccharides. Finally, the performance of six different docking programs (Autodock 3, Autodock Vina, MOE, eHiTS, FlexX and Glide), some of which proved to perform well for particular protein-glycosaminoglycan complexes in previous work, is evaluated on the complete protein-glycosaminoglycan data set from the PDB. This work contributes to widen our knowledge of protein-glycosaminoglycan molecular recognition and could be useful to steer a choice of the strategies to be applied in theoretical studies of these systems.

Carbohydrate-protein interactions: molecular modeling insights

The article reviews the significant contributions to, and the present status of, applications of computational methods for the characterization and prediction of protein-carbohydrate interactions. After a presentation of the specific features of carbohydrate modeling, along with a brief description of the experimental data and general features of carbohydrate-protein interactions, the survey provides a thorough coverage of the available computational methods and tools. At the quantum-mechanical level, the use of both molecular orbitals and density-functional theory is critically assessed. These are followed by a presentation and critical evaluation of the applications of semiempirical and empirical methods: QM/MM, molecular dynamics, free-energy calculations, metadynamics, molecular robotics, and others. The usefulness of molecular docking in structural glycobiology is evaluated by considering recent docking- validation studies on a range of protein targets. The range of applications of these theoretical methods provides insights into the structural, energetic, and mechanistic facets that occur in the course of the recognition processes. Selected examples are provided to exemplify the usefulness and the present limitations of these computational methods in their ability to assist in elucidation of the structural basis underlying the diverse function and biological roles of carbohydrates in their dialogue with proteins. These test cases cover the field of both carbohydrate biosynthesis and glycosyltransferases, as well as glycoside hydrolases. The phenomenon of (macro)molecular recognition is illustrated for the interactions of carbohydrates with such proteins as lectins, monoclonal antibodies, GAG-binding proteins, porins, and viruses.

Exploring the free-energy landscape of carbohydrate-protein complexes: development and validation of scoring functions considering the binding-site topology

Carbohydrates play a key role in a variety of physiological and pathological processes and, hence, represent a rich source for the development of novel therapeutic agents. Being able to predict binding mode and binding affinity is an essential, yet lacking, aspect of the structure-based design of carbohydrate-based ligands. We assembled a diverse data set comprising 273 carbohydrate-protein crystal structures with known binding affinity and evaluated the prediction accuracy of a large collection of well-established scoring and free-energy functions, as well as combinations thereof. Unfortunately, the tested functions were not capable of reproducing binding affinities in the studied complexes. To simplify the complex free-energy surface of carbohydrate-protein systems, we classified the studied proteins according to the topology and solvent exposure of the carbohydrate-binding site into five distinct categories. A free-energy model based on the proposed classification scheme reproduced binding affinities in the carbohydrate data set with an r(2) of 0.71 and root-mean-squared-error of 1.25 kcal/mol (N = 236). The improvement in model performance underlines the significance of the differences in the local micro-environments of carbohydrate-binding sites and demonstrates the usefulness of calibrating free-energy functions individually according to binding-site topology and solvent exposure.

Recent advances in employing molecular modelling to determine the specificity of glycan-binding proteins

Impressive improvements in docking performance can be achieved by applying energy bonuses to poses in which glycan hydroxyl groups occupy positions otherwise preferred by bound waters. In addition, inclusion of glycosidic conformational energies allows unlikely glycan conformations to be appropriately penalized. A method for predicting the binding specificity of glycan-binding proteins has been developed, which is based on grafting glycan branches onto a minimal binding determinant in the binding site. Grafting can be used either to screen virtual libraries of glycans, such as the known glycome, or to identify docked poses of minimal binding determinants that are consistent with specificity data. The reviewed advances allow accurate modelling of carbohydrate-protein 3D co-complexes, but challenges remain in ranking the affinity of congeners.

Deciphering the glycan preference of bacterial lectins by glycan array and molecular docking with validation by microcalorimetry and crystallography

Recent advances in glycobiology revealed the essential role of lectins for deciphering the glycocode by specific recognition of carbohydrates. Integrated multiscale approaches are needed for characterizing lectin specificity: combining on one hand high-throughput analysis by glycan array experiments and systematic molecular docking of oligosaccharide libraries and on the other hand detailed analysis of the lectin/oligosaccharide interaction by x-ray crystallography, microcalorimetry and free energy calculations. The lectins LecB from Pseudomonas aeruginosa and BambL from Burkholderia ambifaria are part of the virulence factors used by the pathogenic bacteria to invade the targeted host. These two lectins are not related but both recognize fucosylated oligosaccharides such as the histo-blood group oligosaccharides of the ABH(O) and Lewis epitopes. The specificities were characterized using semi-quantitative data from glycan array and analyzed by molecular docking with the Glide software. Reliable prediction of protein/oligosaccharide structures could be obtained as validated by existing crystal structures of complexes. Additionally, the crystal structure of BambL/Lewis x was determined at 1.6 Å resolution, which confirms that Lewis x has to adopt a high-energy conformation so as to bind to this lectin. Free energies of binding were calculated using a procedure combining the Glide docking protocol followed by free energy rescoring with the Prime/Molecular Mechanics Generalized Born Surface Area (MM-GBSA) method. The calculated data were in reasonable agreement with experimental free energies of binding obtained by titration microcalorimetry. The established predictive protocol is proposed to rationalize large sets of data such as glycan arrays and to help in lead discovery projects based on such high throughput technology.

Simulation of carbohydrates, from molecular docking to dynamics in water

Modeling of carbohydrates is particularly challenging because of the variety of structures resulting for the high number of monosaccharides and possible linkages and also because of their intrinsic flexibility. The development of carbohydrate parameters for molecular modeling is still an active field. Nowadays, main carbohydrates force fields are GLYCAM06, CHARMM36, and GROMOS 45A4. GLYCAM06 includes the largest choice of compounds and is compatible with the AMBER force fields and associated. Furthermore, AMBER includes tools for the implementation of new parameters. When looking at protein-carbohydrate interaction, the choice of the starting structure is of importance. Such complex can be sometimes obtained from the Protein Data Bank-although the stereochemistry of sugars may require some corrections. When no experimental data is available, molecular docking simulation is generally used to the obtain protein-carbohydrate complex coordinates. As molecular docking parameters are not specifically dedicated to carbohydrates, inaccuracies should be expected, especially for the docking of polysaccharides. This issue can be addressed at least partially by combining molecular docking with molecular dynamics simulation in water.

Solvent structure improves docking prediction in lectin-carbohydrate complexes

Recognition and complex formation between proteins and carbohydrates is a key issue in many important biological processes. Determination of the three-dimensional structure of such complexes is thus most relevant, but particularly challenging because of their usually low binding affinity. In silico docking methods have a long-standing tradition in predicting protein-ligand complexes, and allow a potentially fast exploration of a number of possible protein-carbohydrate complex structures. However, determining which of these predicted complexes represents the correct structure is not always straightforward. In this work, we present a modification of the scoring function provided by AutoDock4, a widely used docking software, on the basis of analysis of the solvent structure adjacent to the protein surface, as derived from molecular dynamics simulations, that allows the definition and characterization of regions with higher water occupancy than the bulk solvent, called water sites. They mimic the interaction held between the carbohydrate -OH groups and the protein. We used this information for an improved docking method in relation to its capacity to correctly predict the protein-carbohydrate complexes for a number of tested proteins, whose ligands range in size from mono- to tetrasaccharide. Our results show that the presented method significantly improves the docking predictions. The resulting solvent-structure-biased docking protocol, therefore, appears as a powerful tool for the design and optimization of development of glycomimetic drugs, while providing new insights into protein-carbohydrate interactions. Moreover, the achieved improvement also underscores the relevance of the solvent structure to the protein carbohydrate recognition process.

In silico mutagenesis and docking study of Ralstonia solanacearum RSL lectin: performance of docking software to predict saccharide binding

In this study, in silico mutagenesis and docking in Ralstonia solanacearum lectin (RSL) were carried out, and the ability of several docking software programs to calculate binding affinity was evaluated. In silico mutation of six amino acid residues (Agr17, Glu28, Gly39, Ala40, Trp76, and Trp81) was done, and a total of 114 in silico mutants of RSL were docked with Me-α-L-fucoside. Our results show that polar residues Arg17 and Glu28, as well as nonpolar amino acids Trp76 and Trp81, are crucial for binding. Gly39 may also influence ligand binding because any mutations at this position lead to a change in the binding pocket shape. The Ala40 residue was found to be the most interesting residue for mutagenesis and can affect the selectivity and/or affinity. In general, the docking software used performs better for high affinity binders and fails to place the binding affinities in the correct order.

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.

Role of water molecules in structure and energetics of Pseudomonas aeruginosa lectin I interacting with disaccharides

Calcium-dependent lectin I from Pseudomonas aeruginosa (PA-IL) binds specifically to oligosaccharides presenting an alpha-galactose residue at their nonreducing end, such as the disaccharides alphaGal1-2betaGalOMe, alphaGal1-3betaGalOMe, and alphaGal1-4betaGalOMe. This provides a unique model for studying the effect of the glycosidic linkage of the ligands on structure and thermodynamics of the complexes by means of experimental and theoretical tools. The structural features of PA-IL in complex with the three disaccharides were established by docking and molecular dynamics simulations and compared with those observed in available crystal structures, including PA-IL.alphaGal1-2betaGalOMe complex, which was solved at 2.4 A resolution and reported herein. The role of a structural bridge water molecule in the binding site of PA-IL was also elucidated through molecular dynamics simulations and free energy calculations. This water molecule establishes three very stable hydrogen bonds with O6 of nonreducing galactose, oxygen from Pro-51 main chain, and nitrogen from Gln-53 main chain of the lectin binding site. Binding free energies for PA-IL in complex with the three disaccharides were investigated, and the results were compared with the experimental data determined by titration microcalorimetry. When the bridge water molecule was included in the free energy calculations, the simulations predicted the correct binding affinity trends with the 1-2-linked disaccharide presenting three times stronger affinity ligand than the other two. These results highlight the role of the water molecule in the binding site of PA-IL and indicate that it should be taken into account when designing glycoderivatives active against P. aeruginosa adhesion.

Computational studies on the interaction of ABO-active saccharides with the norovirus VA387 capsid protein can explain experimental binding data

Norovirus strains are known to cause recurring epidemics of winter vomiting disease. The crystal structure of the capsid protein of VA387, a representative of the clinically important GII.4 genocluster, was recently solved in complex with histo-blood group A- and B-trisaccharides. However, the VA387 strain is known to bind also to other natural carbohydrates for which detailed structural information of the complexes is not available. In this study we have computationally explored the fit of the VA387 with a set of naturally occurring carbohydrate ligands containing a terminal alpha1,2-linked fucose. MD simulations both with explicit and implicit solvent models indicate that type 1 and 3 extensions of the ABO-determinant including ALe(b) and BLe(b) pentasaccharides can be well accommodated in the site. Scoring with Glide XP indicates that the downstream extensions of the ABO-determinants give an increase in binding strength, although the alpha1,2-linked fucose is the single strongest interacting residue. An error was discovered in the geometry of the GalNAc-Gal moiety of the published crystal structure of the A-trisaccharide/VA387 complex. The present modeling of the complexes with histo-blood group A-active structures shows some contacts which provide insight into mutational data, explaining the involvement of I389 and Q331. Our results can be applicable in structure-based design of adhesion inhibitors of noroviruses.

Molecular docking of carbohydrate ligands to antibodies: structural validation against crystal structures

Cell surface glycoproteins play vital roles in cellular homeostasis and disease. Antibody recognition of glycosylation on different cells and pathogens is critically important for immune surveillance. Conversely, adverse immune reactions resulting from antibody-carbohydrate interactions have been implicated in the development of autoimmune diseases and impact areas such as xenotransplantation and cancer treatment. Understanding the nature of antibody-carbohydrate interactions and the method by which saccharides fit into antibody binding sites is important in understanding the recognition process. In silico techniques offer attractive alternatives to experimental methods (X-ray crystallography and NMR) for the study of antibody-carbohydrate complexes. In particular, molecular docking provides information about protein-ligand interactions in systems that are difficult to study with experimental techniques. Before molecular docking can be used to investigate antibody-carbohydrate complexes, validation of an appropriate docking method is required. In this study, four popular docking programs, Glide, AutoDock, GOLD, and FlexX, were assessed for their ability to accurately dock carbohydrates to antibodies. Comparison of top ranking poses with crystal structures highlighted the strengths and weaknesses of these programs. Rigid docking, in which the protein conformation remains static, and flexible docking, where both the protein and ligand are treated as flexible, were compared. This study has revealed that generally molecular docking of carbohydrates to antibodies has been performed best by Glide.

Structural studies of langerin and Birbeck granule: a macromolecular organization model

Dendritic cells, a sentinel immunity cell lineage, include different cell subsets that express various C-type lectins. For example, epidermal Langerhans cells express langerin, and some dermal dendritic cells express DC-SIGN. Langerin is a crucial component of Birbeck granules, the Langerhans cell hallmark organelle, and may have a preventive role toward HIV, by its internalization into Birbeck granules. Since langerin carbohydrate recognition domain (CRD) is crucial for HIV interaction and Birbeck granule formation, we produced the CRD of human langerin and solved its structure at 1.5 A resolution. On this basis gp120 high-mannose oligosaccharide binding has been evaluated by molecular modeling. Hydrodynamic studies reveal a very elongated shape of recombinant langerin extracellular domain (ECD). A molecular model of the langerin ECD, integrating the CRD structure, has been generated and validated by comparison with hydrodynamic parameters. In parallel, Langerhans cells were isolated from human skin. From their analysis by electron microscopy and the langerin ECD model, an ultrastructural organization is proposed for Birbeck granules. To delineate the role of the different langerin domains in Birbeck granule formation, we generated truncated and mutated langerin constructs. After transfection into a fibroblastic cell line, we highlighted, in accordance with our model, the role of the CRD in the membrane zipping occurring in BG formation as well as some contribution of the cytoplasmic domain. Finally, we have shown that langerin ECD triggering with a specific mAb promotes global rearrangements of LC morphology. Our results open the way to the definition of a new membrane deformation mechanism.

Structural basis of the preferential binding for globo-series glycosphingolipids displayed by Pseudomonas aeruginosa lectin I

The opportunistic pathogen Pseudomonas aeruginosa contains several carbohydrate-binding proteins, among which is the P. aeruginosa lectin I (PA-IL), which displays affinity for alpha-galactosylated glycans. Glycan arrays were screened and demonstrated stronger binding of PA-IL toward alphaGal1-4betaGal-terminating structures and weaker binding to alphaGal1-3betaGal ones in order to determine which human glycoconjugates could play a role in the carbohydrate-mediated adhesion of the bacteria. This was confirmed in vivo by testing the binding of the lectin to Burkitt lymphoma cells that present large amounts of globotriaosylceramide antigen Gb3/CD77/P(k). Trisaccharide moieties of Gb3 (alphaGal1-4betaGal1-4Glc) and isoglobotriaosylceramide (alphaGal1-3betaGal1-4Glc) were tested by titration microcalorimetry, and both displayed similar affinity to PA-IL in solution. The crystal structure of PA-IL complexed to alphaGal1-3betaGal1-4Glc trisaccharide has been solved at 1.9-A resolution and revealed how the second galactose residue makes specific contacts with the protein surface. Molecular modeling studies were performed in order to compare the binding mode of PA-IL toward alphaGal1-3Gal with that toward alphaGal1-4Gal. Docking studies demonstrated that alphaGal1-4Gal creates another network of contacts for achieving a very similar affinity, and 10-ns molecular dynamics in explicit water allowed for analyzing the flexibility of each disaccharide ligand in the protein binding site. The higher affinity observed for binding to Gb3 epitope, both in vivo and on glycan array, is likely related to the presentation effect of the oligosaccharide on a surface, since only the Gb3 glycosphingolipid geometry is fully compatible with parallel insertion of neighboring trisaccharide heads in two binding sites of the same tetramer of PA-IL.