Stacking interactions between carbohydrate and protein quantified by combination of theoretical and experimental methods

PeSTo-Carbs: Geometric Deep Learning for Prediction of Protein-Carbohydrate Binding Interfaces

The Protein Structure Transformer (PeSTo), a geometric transformer, has exhibited exceptional performance in predicting protein-protein binding interfaces and distinguishing interfaces with nucleic acids, lipids, small molecules, and ions. In this study, we introduce PeSTo-Carbs, an extension of PeSTo specifically engineered to predict protein-carbohydrate binding interfaces. We evaluate the performance of this approach using independent test sets and compare them with those of previous methods. Furthermore, we highlight the model's capability to specialize in predicting interfaces involving cyclodextrins, a biologically and pharmaceutically significant class of carbohydrates. Our method consistently achieves remarkable accuracy despite the scarcity of available structural data for cyclodextrins.

Glycan-specific molecularly imprinted polymers towards cancer diagnostics: merits, applications, and future perspectives

Aberrant glycans are a hallmark of cancer states. Notably, emerging evidence has demonstrated that the diagnosis of cancers with tumour-specific glycan patterns holds great potential to address unmet medical needs, especially in improving diagnostic sensitivity and selectivity. However, despite vast glycans having been identified as potent markers, glycan-based diagnostic methods remain largely limited in clinical practice. There are several reasons that prevent them from reaching the market, and the lack of anti-glycan antibodies is one of the most challenging hurdles. With the increasing need for accelerating the translational process, numerous efforts have been made to find antibody alternatives, such as lectins, boronic acids and aptamers. However, issues concerning affinity, selectivity, stability and versatility are yet to be fully addressed. Molecularly imprinted polymers (MIPs), synthetic antibody mimics with tailored cavities for target molecules, hold the potential to revolutionize this dismal progress. MIPs can bind a wide range of glycan markers, even those without specific antibodies. This capacity effectively broadens the clinical applicability of glycan-based diagnostics. Additionally, glycoform-resolved diagnosis can also be achieved through customization of MIPs, allowing for more precise diagnostic applications. In this review, we intent to introduce the current status of glycans as potential biomarkers and critically evaluate the challenges that hinder the development of in vitro diagnostic assays, with a particular focus on glycan-specific recognition entities. Moreover, we highlight the key role of MIPs in this area and provide examples of their successful use. Finally, we conclude the review with the remaining challenges, future outlook, and emerging opportunities.

The dengue-specific immune response and antibody identification with machine learning

Dengue virus poses a serious threat to global health and there is no specific therapeutic for it. Broadly neutralizing antibodies recognizing all serotypes may be an effective treatment. High-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) and bioinformatic analysis enable in-depth understanding of the B-cell immune response. Here, we investigate the dengue antibody response with these technologies and apply machine learning to identify rare and underrepresented broadly neutralizing antibody sequences. Dengue immunization elicited the following signatures on the antibody repertoire: (i) an increase of CDR3 and germline gene diversity; (ii) a change in the antibody repertoire architecture by eliciting power-law network distributions and CDR3 enrichment in polar amino acids; (iii) an increase in the expression of JNK/Fos transcription factors and ribosomal proteins. Furthermore, we demonstrate the applicability of computational methods and machine learning to AIRR-seq datasets for neutralizing antibody candidate sequence identification. Antibody expression and functional assays have validated the obtained results.

Modulation of protein-saccharide interactions by deep-sea osmolytes under high pressure stress

Deep-sea organisms must cope with high hydrostatic pressures (HHP) up to the kbar regime to control their biomolecular processes. To alleviate the adverse effects of HHP on protein stability most organisms use high amounts of osmolytes. Little is known about the effects of these high concentrations on ligand binding. We studied the effect of the deep-sea osmolytes trimethylamine-N-oxide, glycine, and glycine betaine on the binding between lysozyme and the tri-saccharide NAG3, employing experimental and theoretical tools to reveal the combined effect of osmolytes and HHP on the conformational dynamics, hydration changes, and thermodynamics of the binding process. Due to their different chemical makeup, these cosolutes modulate the protein-sugar interaction in different ways, leading to significant changes in the binding constant and its pressure dependence. These findings suggest that deep-sea organisms may down- and up-regulate reactions in response to HHP stress by altering the concentration and type of the intracellular osmolyte.

Insights into the Mechanism of Tryptophan Fluorescence Quenching due to Synthetic Crowding Agents: A Combined Experimental and Computational Study

Intrinsic tryptophan fluorescence spectroscopy is an important tool for examining the effects of molecular crowding and confinement on the structure, dynamics, and function of proteins. Synthetic crowders such as dextran, ficoll, polyethylene glycols, polyvinylpyrrolidone, and their respective monomers are used to mimic crowded intracellular environments. Interactions of these synthetic crowders with tryptophan and the subsequent impact on its fluorescence properties are therefore critically important for understanding the possible interference created by these crowders. In the present study, the effects of polymer and monomer crowders on tryptophan fluorescence were assessed by using experimental and computational approaches. The results of this study demonstrated that both polymer and monomer crowders have an impact on the tryptophan fluorescence intensity; however, the molecular mechanisms of quenching were different. Using Stern-Volmer plots and a temperature variation study, a physical basis for the quenching mechanism of commonly used synthetic crowders was established. The quenching of free tryptophan was found to involve static, dynamic, and sphere-of-action mechanisms. In parallel, computational studies employing Kohn-Sham density functional theory provided a deeper insight into the effects of intermolecular interactions and solvation, resulting in differing quenching modes for these crowders. Taken together, the study offers new physical insights into the quenching mechanisms of some commonly used monomer and polymer synthetic crowders.

Multifaceted Computational Modeling in Glycoscience

Glycoscience assembles all the scientific disciplines involved in studying various molecules and macromolecules containing carbohydrates and complex glycans. Such an ensemble involves one of the most extensive sets of molecules in quantity and occurrence since they occur in all microorganisms and higher organisms. Once the compositions and sequences of these molecules are established, the determination of their three-dimensional structural and dynamical features is a step toward understanding the molecular basis underlying their properties and functions. The range of the relevant computational methods capable of addressing such issues is anchored by the specificity of stereoelectronic effects from quantum chemistry to mesoscale modeling throughout molecular dynamics and mechanics and coarse-grained and docking calculations. The Review leads the reader through the detailed presentations of the applications of computational modeling. The illustrations cover carbohydrate-carbohydrate interactions, glycolipids, and N- and O-linked glycans, emphasizing their role in SARS-CoV-2. The presentation continues with the structure of polysaccharides in solution and solid-state and lipopolysaccharides in membranes. The full range of protein-carbohydrate interactions is presented, as exemplified by carbohydrate-active enzymes, transporters, lectins, antibodies, and glycosaminoglycan binding proteins. A final section features a list of 150 tools and databases to help address the many issues of structural glycobioinformatics.

gmx_MMPBSA: A New Tool to Perform End-State Free Energy Calculations with GROMACS

Molecular mechanics/Poisson-Boltzmann (Generalized-Born) surface area is one of the most popular methods to estimate binding free energies. This method has been proven to balance accuracy and computational efficiency, especially when dealing with large systems. As a result of its popularity, several programs have been developed for performing MM/PB(GB)SA calculations within the GROMACS community. These programs, however, present several limitations. Here we present gmx_MMPBSA, a new tool to perform end-state free energy calculations from GROMACS molecular dynamics trajectories. gmx_MMPBSA provides the user with several options, including binding free energy calculations with different solvation models (PB, GB, or 3D-RISM), stability calculations, computational alanine scanning, entropy corrections, and binding free energy decomposition. Noteworthy, several promising methodologies to calculate relative binding free energies such as alanine scanning with variable dielectric constant and interaction entropy have also been implemented in gmx_MMPBSA. Two additional tools-gmx_MMPBSA_test and gmx_MMPBSA_ana-have been integrated within gmx_MMPBSA to improve its usability. Multiple illustrating examples can be accessed through gmx_MMPBSA_test, while gmx_MMPBSA_ana provides fast, easy, and efficient access to different graphics plotted from gmx_MMPBSA output files. The latest version (v1.4.3, 26/05/2021) is available free of charge (documentation, test files, and tutorials included) at https://github.com/Valdes-Tresanco-MS/gmx_MMPBSA.

Systematic review on lectin-based electrochemical biosensors for clinically relevant carbohydrates and glycoconjugates

Carbohydrates and glycoconjugates are involved in numerous natural and pathological metabolic processes, and the precise elucidation of their biochemical functions has been supported by smart technologies assembled with lectins, i.e., ubiquitous proteins of nonimmune origin with carbohydrate-specific domains. When lectins are anchored on suitable electrochemical transducers, sensitive and innovative bioanalytical tools (lectin-based biosensors) are produced, with the ability to screen target sugars at molecular levels. In addition to the remarkable electroanalytical sensitivity, these devices associate specificity, precision, stability, besides the possibility of miniaturization and portability, which are special features required for real-time and point-of-care measurements. The mentioned attributes can be improved by combining lectins with biocompatible 0-3D semiconductors derived from carbon, metal nanoparticles, polymers and their nanocomposites, or employing labeled biomolecules. This systematic review aims to substantiate and update information on the progress made with lectin-based biosensors designed for electroanalysis of clinically relevant carbohydrates and glycoconjugates (glycoproteins, pathogens and cancer biomarkers), highlighting their main detection principles and performance in highly complex biological milieus. Moreover, particular emphasis is given to the main advantages and limitations of the reported devices, as well as the new trends for the current demands. We believe that this review will support and encourage more cutting-edge research involving lectin-based electrochemical biosensors.

Visualization of hydrogen atoms in a perdeuterated lectin-fucose complex reveals key details of protein-carbohydrate interactions

Carbohydrate-binding proteins from pathogenic bacteria and fungi have been shown to be implicated in various pathological processes, where they interact with glycans present on the surface of the host cells. These interactions are part of the initial processes of infection of the host and are very important to study at the atomic level. Here, we report the room temperature neutron structures of PLL lectin from Photorhabdus laumondii in its apo form and in complex with deuterated L-fucose, which is, to our knowledge, the first neutron structure of a carbohydrate-binding protein in complex with a fully deuterated carbohydrate ligand. A detailed structural analysis of the lectin-carbohydrate interactions provides information on the hydrogen bond network, the role of water molecules, and the extent of the CH-π stacking interactions between fucose and the aromatic amino acids in the binding site.

Structure of a consensus chitin-binding domain revealed by solution NMR

Chitin-binding proteins (CBPs) are a versatile group of proteins found in almost every organism on earth. CBPs are involved in enzymatic carbohydrate degradation and also serve as templating scaffolds in the exoskeleton of crustaceans and insects. One specific chitin-binding motif found across a wide range of arthropods' exoskeletons is the "extended Rebers and Riddiford" consensus (R&R), whose mechanism of chitin binding remains unclear. Here, we report the 3D structure and molecular level interactions of a chitin-binding domain (CBD-γ) located in a CBP from the beak of the jumbo squid Dosidicus gigas. This CBP is one of four chitin-binding proteins identified in the beak mouthpart of D. gigas and is believed to interact with chitin to form a scaffold network that is infiltrated with a second set of structural proteins during beak maturation. We used solution state NMR spectroscopy to elucidate the molecular interactions between CBD-γ and the soluble chitin derivative pentaacetyl-chitopentaose (PCP), and find that folding of CBD-γ is triggered upon its interaction with PCP. To our knowledge, this is the first experimental 3D structure of a CBP containing the R&R consensus motif, which can be used as a template to understand in more details the role of the R&R motif found in a wide range of CBP-chitin complexes. The present structure also provides molecular information for biomimetic synthesis of graded biomaterials using aqueous-based chemistry and biopolymers.

Pick's Tau Fibril Shows Multiple Distinct PET Probe Binding Sites: Insights from Computational Modelling

In recent years, it has been realized that the tau protein is a key player in multiple neurodegenerative diseases. Positron emission tomography (PET) radiotracers that bind to tau filaments in Alzheimer’s disease (AD) are in common use, but PET tracers binding to tau filaments of rarer, age-related dementias, such as Pick’s disease, have not been widely explored. To design disease-specific and tau-selective PET tracers, it is important to determine where and how PET tracers bind to tau filaments. In this paper, we present the first molecular modelling study on PET probe binding to the structured core of tau filaments from a patient with Pick’s disease (Tau^PiD). We have used docking, molecular dynamics simulations, binding-affinity and tunnel calculations to explore Tau^PiD binding sites, binding modes, and binding energies of PET probes (AV-1451, MK-6240, PBB3, PM-PBB3, THK-5351 and PiB) with Tau^PiD. The probes bind to Tau^PiD at multiple surface binding sites as well as in a cavity binding site. The probes show unique surface binding patterns, and, out of them all, PM-PBB3 proves to bind the strongest. The findings suggest that our computational workflow of structural and dynamic details of the tau filaments has potential for the rational design of Tau^PiD specific PET tracers.

Three-Dimensional Structures of Carbohydrates and Where to Find Them

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

The CH-π Interaction in Protein-Carbohydrate Binding: Bioinformatics and In Vitro Quantification

The molecular recognition of carbohydrates by proteins plays a key role in many biological processes including immune response, pathogen entry into a cell, and cell-cell adhesion (e.g., in cancer metastasis). Carbohydrates interact with proteins mainly through hydrogen bonding, metal-ion-mediated interaction, and non-polar dispersion interactions. The role of dispersion-driven CH-π interactions (stacking) in protein-carbohydrate recognition has been underestimated for a long time considering the polar interactions to be the main forces for saccharide interactions. However, over the last few years it turns out that non-polar interactions are equally important. In this study, we analyzed the CH-π interactions employing bioinformatics (data mining, structural analysis), several experimental (isothermal titration calorimetry (ITC), X-ray crystallography), and computational techniques. The Protein Data Bank (PDB) has been used as a source of structural data. The PDB contains over 12 000 protein complexes with carbohydrates. Stacking interactions are very frequently present in such complexes (about 39 % of identified structures). The calculations and the ITC measurement results suggest that the CH-π stacking contribution to the overall binding energy ranges from 4 up to 8 kcal mol^-1 . All the results show that the stacking CH-π interactions in protein-carbohydrate complexes can be considered to be a driving force of the binding in such complexes.

Expression and characterization of a novel alginate-binding protein: A promising tool for investigating alginate

Alginate is a commercially important polysaccharide widely applied in various industries. Carbohydrate-binding proteins could be utilized as desirable tools in the investigation and further applications of polysaccharides. Few alginate-binding proteins have hitherto been characterized and reported. In the present study, a novel alginate-binding protein ABP_Wf, consisting of two "orphan" carbohydrate-binding modules, was cloned from a predicted alginate utilization locus of marine bacterium Wenyingzhuangia funcanilytica, and expressed in Escherichia coli. ABP_Wf exhibited a specific binding capacity to alginate, and the association constant (K_a) and affinity (K_D) were 1.94 × 10³ M^-1s^-1 and 1.16 × 10^-6 M. It was confirmed that the binding capacity of ABP_Wf to alginate is attributed to its constituent CBM16 domain rather than the CBM44 domain. The potentials of ABP_Wf in the semi-quantitative detection and the in situ visualization of alginate were evaluated, which implied that ABP_Wf could be served as a promising tool for investigating alginate.

Crystal structures of a β-trefoil lectin from Entamoeba histolytica in monomeric and a novel disulfide bond-mediated dimeric forms

β-Trefoil lectins are galactose/N-acetyl galactosamine specific lectins, which are widely distributed across all kingdoms of life and are known to perform several important functions. However, there is no report available on the characterization of these lectins from protozoans. We have performed structural and biophysical studies on a β-trefoil lectin from Entamoeba histolytica (EntTref), which exists as a mixture of monomers and dimers in solution. Further, we have determined the affinities of EntTref for rhamnose, galactose and different galactose-linked sugars. We obtained the crystal structure of EntTref in a sugar-free form (EntTref_apo) and a rhamnose-bound form (EntTref_rham). A novel Cys residue-mediated dimerization was revealed in the crystal structure of EntTref_apo while the structure of EntTref_rham provided the structural basis for the recognition of rhamnose by a β-trefoil lectin for the first time. To the best of our knowledge, this is the only report of the structural, functional and biophysical characterization of a β-trefoil lectin from a protozoan source and the first report of Cys-mediated dimerization in this class of lectins.

The challenges of glycan recognition with natural and artificial receptors

Glycans - simple or complex carbohydrates - play key roles as recognition determinants and modulators of numerous physiological and pathological processes. Thus, many biotechnological, diagnostic and therapeutic opportunities abound for molecular recognition entities that can bind glycans with high selectivity and affinity. This review begins with an overview of the current biologically and synthetically derived glycan-binding scaffolds that include antibodies, lectins, aptamers and boronic acid-based entities. It is followed by a more detailed discussion on various aspects of their generation, structure and recognition properties. It serves as the basis for highlighting recent key developments and technical challenges that must be overcome in order to fully deal with the specific recognition of a highly diverse and complex range of glycan structures.

Crowder-Induced Conformational Ensemble Shift in Escherichia coli Prolyl-tRNA Synthetase

The effect of molecular crowding on the structure and function of Escherichia coli prolyl-transfer RNA synthetase (Ec ProRS), a member of the aminoacyl-transfer RNA synthetase family, has been investigated using a combined experimental and theoretical method. Ec ProRS is a multidomain enzyme; coupled-domain dynamics are essential for efficient catalysis. To gain insight into the mechanistic detail of the crowding effect, kinetic studies were conducted with varying concentrations and sizes of crowders. In parallel, spectroscopic and quantum chemical studies were employed to probe the "soft interactions" between crowders and protein side chains. Finally, the dynamics of the dimeric protein was examined in the presence of crowders using a long-duration (70 ns) classical molecular dynamic simulations. The results of the simulations revealed a shift in the conformational ensemble, which is consistent with the preferential exclusion of cosolutes. The "soft interactions" model of the crowding effect also explained the alteration in kinetic parameters. In summary, the study found that the effects of molecular crowding on both conformational dynamics and catalytic function are correlated in the multidomain Ec ProRS, an enzyme that is central to protein synthesis in all living cells. This study affirmed that large and small cosolutes have considerable impacts on the structure, dynamics, and function of modular proteins and therefore must be considered for stabilizing protein-based pharmaceuticals and industrial enzymes.

Effect of Noncanonical Amino Acids on Protein-Carbohydrate Interactions: Structure, Dynamics, and Carbohydrate Affinity of a Lectin Engineered with Fluorinated Tryptophan Analogs

Protein–carbohydrate interactions play crucial roles in biology. Understanding and modifying these interactions is of major interest for fighting many diseases. We took a synthetic biology approach and incorporated noncanonical amino acids into a bacterial lectin to modulate its interactions with carbohydrates. We focused on tryptophan, which is prevalent in carbohydrate binding sites. The exchange of the tryptophan residues with analogs fluorinated at different positions resulted in three distinctly fluorinated variants of the lectin from Ralstonia solanacearum. We observed differences in stability and affinity toward fucosylated glycans and rationalized them by X-ray and modeling studies. While fluorination decreased the aromaticity of the indole ring and, therefore, the strength of carbohydrate–aromatic interactions, additional weak hydrogen bonds were formed between fluorine and the ligand hydroxyl groups. Our approach opens new possibilities to engineer carbohydrate receptors.

Assessing the Performance of MM/PBSA, MM/GBSA, and QM-MM/GBSA Approaches on Protein/Carbohydrate Complexes: Effect of Implicit Solvent Models, QM Methods, and Entropic Contributions

Rapid and accurate binding affinity prediction of protein-carbohydrate complexes is a major challenge in glycomimetics design. Among the existing computational techniques, end-point methods have received considerable interest because of their low computational cost. However, significant obstacles remain when such methods are applied to protein-glycan complexes. This article reports the performance of end-point free-energy calculation methods: molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA), MM/generalized Born surface area (MM/GBSA), and quantum mechanics-MM/GBSA (QM-MM/GBSA) on monosaccharides bound to RSL lectin from Ralstonia solanacearum. A careful investigation of the molecular dynamics simulation length, van der Waals radii sets, GB models, QM Hamiltonians, and entropic compensation has been made, and the results are compared with the experimental binding free energies from isothermal titration calorimetry/surface plasmon resonance measurements. The binding free energies using implicit solvent methods are found to be sensitive to the simulation length, radii set, GB model, and QM Hamiltonian. A simulation length of 10 ns using the radii set mbondi provides the best agreement with the experimental values ( r² = 0.96) by MM/PBSA. The GB^HCT model is in accord with the experimental values in MM/GBSA ( r² = 0.91) or in combination with parameterized model number 6 (PM6) ( r² = 0.98) in QM-MM/GBSA. Out of 12 QM Hamiltonians tested, PM6, density functional theory-based tight binding (DFTB), and their variants proved to be more efficient than other semiempirical methods. These methods perform equally well in predicting both absolute and relative binding free energies.

A combined computational-experimental approach to define the structural origin of antibody recognition of sialyl-Tn, a tumor-associated carbohydrate antigen

Anti-carbohydrate monoclonal antibodies (mAbs) hold great promise as cancer therapeutics and diagnostics. However, their specificity can be mixed, and detailed characterization is problematic, because antibody-glycan complexes are challenging to crystallize. Here, we developed a generalizable approach employing high-throughput techniques for characterizing the structure and specificity of such mAbs, and applied it to the mAb TKH2 developed against the tumor-associated carbohydrate antigen sialyl-Tn (STn). The mAb specificity was defined by apparent K_D values determined by quantitative glycan microarray screening. Key residues in the antibody combining site were identified by site-directed mutagenesis, and the glycan-antigen contact surface was defined using saturation transfer difference NMR (STD-NMR). These features were then employed as metrics for selecting the optimal 3D-model of the antibody-glycan complex, out of thousands plausible options generated by automated docking and molecular dynamics simulation. STn-specificity was further validated by computationally screening of the selected antibody 3D-model against the human sialyl-Tn-glycome. This computational-experimental approach would allow rational design of potent antibodies targeting carbohydrates.

Influence of Trp flipping on carbohydrate binding in lectins. An example on Aleuria aurantia lectin AAL

Protein-carbohydrate interactions are very often mediated by the stacking CH-π interactions involving the side chains of aromatic amino acids such as tryptophan (Trp), tyrosine (Tyr) or phenylalanine (Phe). Especially suitable for stacking is the Trp residue. Analysis of the PDB database shows Trp stacking for 265 carbohydrate or carbohydrate like ligands in 5 208 Trp containing motives. An appropriate model system to study such an interaction is the AAL lectin family where the stacking interactions play a crucial role and are thought to be a driving force for carbohydrate binding. In this study we present data showing a novel finding in the stacking interaction of the AAL Trp side chain with the carbohydrate. High resolution X-ray structure of the AAL lectin from Aleuria aurantia with α-methyl-l-fucoside ligand shows two possible Trp side chain conformations with the same occupation in electron density. The in silico data shows that the conformation of the Trp side chain does not influence the interaction energy despite the fact that each conformation creates interactions with different carbohydrate CH groups. Moreover, the PDB data search shows that the conformations are almost equally distributed across all Trp-carbohydrate complexes, which would suggest no substantial preference for one conformation over another.

Molecular Simulations of Carbohydrates with a Fucose-Binding Burkholderia ambifaria Lectin Suggest Modulation by Surface Residues Outside the Fucose-Binding Pocket

Burkholderia ambifaria is an opportunistic respiratory pathogen belonging to the Burkholderia cepacia complex, a collection of species responsible for the rapidly fatal cepacia syndrome in cystic fibrosis patients. A fucose-binding lectin identified in the B. ambifaria genome, BambL, is able to adhere to lung tissue, and may play a role in respiratory infection. X-ray crystallography has revealed the bound complex structures for four fucosylated human blood group epitopes (blood group B, H type 1, H type 2, and Le^x determinants). The present study employed computational approaches, including docking and molecular dynamics (MD), to extend the structural analysis of BambL-oligosaccharide complexes to include four additional blood group saccharides (A, Le^a, Le^b, and Le^y) and a library of blood-group-related carbohydrates. Carbohydrate recognition is dominated by interactions with fucose via a hydrogen-bonding network involving Arg15, Glu26, Ala38, and Trp79 and a stacking interaction with Trp74. Additional hydrogen bonds to non-fucose residues are formed with Asp30, Tyr35, Thr36, and Trp74. BambL recognition is dominated by interactions with fucose, but also features interactions with other parts of the ligands that may modulate specificity or affinity. The detailed computational characterization of the BambL carbohydrate-binding site provides guidelines for the future design of lectin inhibitors.

Calculations of the absolute binding free energies for Ralstonia solanacearum lectins bound with methyl-α-l-fucoside at molecular mechanical and quantum mechanical/molecular mechanical levels

In this work, both a molecular mechanical (MM) method and a hybrid quantum mechanical/molecular mechanical (QM/MM) method have been applied in the study of the binding affinities of methyl-α-l-fucoside to Ralstonia solanacearum lectins.

Cell wall glycopolymers of Firmicutes and their role as nonprotein adhesins

Cell wall glycopolymers (CWGs) of gram-positive bacteria have gained increasing interest with respect to their role in colonization and infection. In most gram-positive pathogens they constitute a large fraction of the cell wall biomass and represent major cell envelope determinants. Depending on their chemical structure they modulate interaction with complement factors and play roles in immune evasion or serve as nonprotein adhesins that mediate, especially under dynamic conditions, attachment to different host cell types. In particular, covalently peptidoglycan-attached CWGs that extend well above the cell wall seem to interact with glyco-receptors on host cell surfaces. For example, in the case of Staphylococcus aureus, the cell wall-attached teichoic acid (WTA) has been identified as a major CWG adhesin. A recent report indicates that a type-F scavenger receptor, termed SR-F1 (SREC-I), is the predominant WTA receptor in the nasal cavity and that WTA-SREC-I interaction plays an important role in S. aureus nasal colonization. Therefore, understanding the role of CWGs in complex processes that mediate colonization and infection will allow novel insights into the mechanisms of host-microbiota interaction.

The Hidden Conformation of Lewis x, a Human Histo-Blood Group Antigen, Is a Determinant for Recognition by Pathogen Lectins

Histo-blood group epitopes are fucosylated branched oligosaccharides with well-defined conformations in solution that are recognized by receptors, such as lectins from pathogens. We report here the results of a series of experimental and computational endeavors revealing the unusual distortion of histo-blood group antigens by bacterial and fungal lectins. The Lewis x trisaccharide adopts a rigid closed conformation in solution, while crystallography and molecular dynamics reveal several higher energy open conformations when bound to the Ralstonia solanacearum lectin, which is in agreement with thermodynamic and kinetic measurements. Extensive molecular dynamics simulations confirm rare transient Le(x) openings in solution, frequently assisted by distortion of the central N-acetyl-glucosamine ring. Additional directed molecular dynamic trajectories revealed the role of a conserved tryptophan residue in guiding the fucose into the binding site. Our findings show that conformational adaptation of oligosaccharides is of paramount importance in cell recognition and should be considered when designing anti-infective glyco-compounds.

Anomer-Specific Recognition and Dynamics in a Fucose-Binding Lectin

Sugar binding by a cell surface ∼29 kDa lectin (RSL) from the bacterium Ralstonia solanacearum was characterized by NMR spectroscopy. The complexes formed with four monosaccharides and four fucosides were studied. Complete resonance assignments and backbone dynamics were determined for RSL in the sugar-free form and when bound to l-fucose or d-mannose. RSL was found to interact with both the α- and the β-anomer of l-fucose and the "fucose like" sugars d-arabinose and l-galactose. Peak splitting was observed for some resonances of the binding site residues. The assignment of the split signals to the α- or β-anomer was confirmed by comparison with the spectra of RSL bound to methyl-α-l-fucoside or methyl-β-l-fucoside. The backbone dynamics of RSL were sensitive to the presence of ligand, with the protein adopting a more compact structure upon binding to l-fucose. Taking advantage of tryptophan residues in the binding sites, we show that the indole resonance is an excellent reporter on ligand binding. Each sugar resulted in a distinct signature of chemical shift perturbations, suggesting that tryptophan signals are a sufficient probe of sugar binding.

Aromatic-Mediated Carbohydrate Recognition in Processive Serratia marcescens Chitinases

Microorganisms use a host of enzymes, including processive glycoside hydrolases, to deconstruct recalcitrant polysaccharides to sugars. Processive glycoside hydrolases closely associate with polymer chains and repeatedly cleave glycosidic linkages without dissociating from the crystalline surface after each hydrolytic step; they are typically the most abundant enzymes in both natural secretomes and industrial cocktails by virtue of their significant hydrolytic potential. The ubiquity of aromatic residues lining the enzyme catalytic tunnels and clefts is a notable feature of processive glycoside hydrolases. We hypothesized that these aromatic residues have uniquely defined roles, such as substrate chain acquisition and binding in the catalytic tunnel, that are defined by their local environment and position relative to the substrate and the catalytic center. Here, we investigated this hypothesis with variants of Serratia marcescens family 18 processive chitinases ChiA and ChiB. We applied molecular simulation and free energy calculations to assess active site dynamics and ligand binding free energies. Isothermal titration calorimetry provided further insight into enthalpic and entropic contributions to ligand binding free energy. Thus, the roles of six aromatic residues, Trp-167, Trp-275, and Phe-396 in ChiA, and Trp-97, Trp-220, and Phe-190 in ChiB, have been examined. We observed that point mutation of the tryptophan residues to alanine results in unfavorable changes in the free energy of binding relative to wild-type. The most drastic effects were observed for residues positioned at the "entrances" of the deep substrate-binding clefts and known to be important for processivity. Interestingly, phenylalanine mutations in ChiA and ChiB had little to no effect on chito-oligomer binding, in accordance with the limited effects of their removal on chitinase functionality.

Carbohydrate-Aromatic Interactions in Proteins

Protein-carbohydrate interactions play pivotal roles in health and disease. However, defining and manipulating these interactions has been hindered by an incomplete understanding of the underlying fundamental forces. To elucidate common and discriminating features in carbohydrate recognition, we have analyzed quantitatively X-ray crystal structures of proteins with noncovalently bound carbohydrates. Within the carbohydrate-binding pockets, aliphatic hydrophobic residues are disfavored, whereas aromatic side chains are enriched. The greatest preference is for tryptophan with an increased prevalence of 9-fold. Variations in the spatial orientation of amino acids around different monosaccharides indicate specific carbohydrate C-H bonds interact preferentially with aromatic residues. These preferences are consistent with the electronic properties of both the carbohydrate C-H bonds and the aromatic residues. Those carbohydrates that present patches of electropositive saccharide C-H bonds engage more often in CH-π interactions involving electron-rich aromatic partners. These electronic effects are also manifested when carbohydrate-aromatic interactions are monitored in solution: NMR analysis indicates that indole favorably binds to electron-poor C-H bonds of model carbohydrates, and a clear linear free energy relationships with substituted indoles supports the importance of complementary electronic effects in driving protein-carbohydrate interactions. Together, our data indicate that electrostatic and electronic complementarity between carbohydrates and aromatic residues play key roles in driving protein-carbohydrate complexation. Moreover, these weak noncovalent interactions influence which saccharide residues bind to proteins, and how they are positioned within carbohydrate-binding sites.

Crystal structures of Mycobacterium tuberculosis GlgE and complexes with non-covalent inhibitors

GlgE is a bacterial maltosyltransferase that catalyzes the elongation of a cytosolic, branched α-glucan. In Mycobacterium tuberculosis (M. tb), inactivation of GlgE (Mtb GlgE) results in the rapid death of the organism due to a toxic accumulation of the maltosyl donor, maltose-1-phosphate (M1P), suggesting that GlgE is an intriguing target for inhibitor design. In this study, the crystal structures of the Mtb GlgE in a binary complex with maltose and a ternary complex with maltose and a maltosyl-acceptor molecule, maltohexaose, were solved to 3.3 Å and 4.0 Å, respectively. The maltohexaose structure reveals a dominant site for α-glucan binding. To obtain more detailed interactions between first generation, non-covalent inhibitors and GlgE, a variant Streptomyces coelicolor GlgEI (Sco GlgEI-V279S) was made to better emulate the Mtb GlgE M1P binding site. The structure of Sco GlgEI-V279S complexed with α-maltose-C-phosphonate (MCP), a non-hydrolyzable substrate analogue, was solved to 1.9 Å resolution, and the structure of Sco GlgEI-V279S complexed with 2,5-dideoxy-3-O-α-D-glucopyranosyl-2,5-imino-D-mannitol (DDGIM), an oxocarbenium mimic, was solved to 2.5 Å resolution. These structures detail important interactions that contribute to the inhibitory activity of these compounds, and provide information on future designs that may be exploited to improve upon these first generation GlgE inhibitors.

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.

Dual modes of membrane binding direct pore formation by Streptolysin O

Effector translocation is central to the virulence of many bacterial pathogens, including Streptococcus pyogenes, which utilizes the cholesterol-dependent cytolysin Streptolysin O (SLO) to translocate the NAD(+) glycohydrolase SPN into host cells during infection. SLO's translocation activity does not require host cell membrane cholesterol or pore formation by SLO, yet SLO does form pores during infection via a cholesterol-dependent mechanism. Although cholesterol was considered the primary receptor for SLO, SLO's membrane-binding domain also encodes a putative carbohydrate-binding site, implicating a potential glycan receptor in binding and pore formation. Analysis of carbohydrate-binding site SLO mutants and carbohydrate-defective cell lines revealed that glycan recognition is involved in SLO's pore formation pathway and is an essential step when SLO is secreted by non-adherent bacteria, as occurs during lysis of erythrocytes. However, SLO also recognizes host cell membranes via a second mechanism when secreted from adherent bacteria, which requires co-secretion of SPN but not glycan binding by SLO. This SPN-mediated membrane binding of SLO correlates with SPN translocation, and requires SPN's non-enzymatic domain, which is predicted to adopt the structure of a carbohydrate-binding module. SPN-dependent membrane binding also promotes pore formation by SLO, demonstrating that pore formation can occur by distinct pathways during infection.

Evaluation of Selected Classical Force Fields for Alchemical Binding Free Energy Calculations of Protein-Carbohydrate Complexes

Protein-carbohydrate recognition is crucial in many vital biological processes including host-pathogen recognition, cell-signaling, and catalysis. Accordingly, computational prediction of protein-carbohydrate binding free energies is of enormous interest for drug design. However, the accuracy of current force fields (FFs) for predicting binding free energies of protein-carbohydrate complexes is not well understood owing to technical challenges such as the highly polar nature of the complexes, anomerization, and conformational flexibility of carbohydrates. The present study evaluated the performance of alchemical predictions of binding free energies with the GAFF1.7/AM1-BCC and GLYCAM06j force fields for modeling protein-carbohydrate complexes. Mean unsigned errors of 1.1 ± 0.06 (GLYCAM06j) and 2.6 ± 0.08 (GAFF1.7/AM1-BCC) kcal·mol(-1) are achieved for a large data set of monosaccharide ligands for Ralstonia solanacearum lectin (RSL). The level of accuracy provided by GLYCAM06j is sufficient to discriminate potent, moderate, and weak binders, a goal that has been difficult to achieve through other scoring approaches. Accordingly, the protocols presented here could find useful applications in carbohydrate-based drug and vaccine developments.

The sweet quartet: Binding of fucose to the norovirus capsid

Human noroviruses bind histo-blood group antigens (HBGAs) and this interaction is thought to be important for an infection. We identified two additional fucose-binding pockets (termed fucose-3/4 sites) on a genogroup II human (GII.10) norovirus-protruding (P) dimer using X-ray crystallography. Fucose-3/4 sites were located between two previously determined HBGA binding pockets (termed fucose-1/2 sites). We found that four fucose molecules were capable of binding altogether at fucose-1/2/3/4 sites on the P dimer, though the fucose molecules bound in a dose-dependent and step-wise manner. We also showed that HBGA B-trisaccharide molecules bound in a similar way at the fucose-1/2 sites. Interestingly, we discovered that the monomers of the P dimer were asymmetrical in an unliganded state and when a single B-trisaccharide molecule bound, but were symmetrical when two B-trisaccharide molecules bound. We postulate that the symmetrical dimers might favor HBGA binding interactions at fucose-1/2 sites.

Landscape of π-π and sugar-π contacts in DNA-protein interactions

There were 1765 contacts identified between DNA nucleobases or deoxyribose and cyclic (W, H, F, Y) or acyclic (R, E, D) amino acids in 672 X-ray structures of DNA-protein complexes. In this first study to compare π-interactions between the cyclic and acyclic amino acids, visual inspection was used to categorize amino acid interactions as nucleobase π-π (according to biological edge) or deoxyribose sugar-π (according to sugar edge). Overall, 54% of contacts are nucleobase π-π interactions, which involve all amino acids, but are more common for Y, F, and R, and involve all DNA nucleobases with similar frequencies. Among binding arrangements, cyclic amino acids prefer more planar (stacked) π-systems than the acyclic counterparts. Although sugar-π interactions were only previously identified with the cyclic amino acids and were found to be less common (38%) than nucleobase-cyclic amino acid contacts, sugar-π interactions are more common than nucleobase π-π contacts for the acyclic series (61% of contacts). Similar to DNA-protein π-π interactions, sugar-π contacts most frequently involve Y and R, although all amino acids adopt many binding orientations relative to deoxyribose. These DNA-protein π-interactions stabilize biological systems, by up to approximately -40 kJ mol(-1) for neutral nucleobase or sugar-amino acid interactions, but up to approximately -95 kJ mol(-1) for positively or negatively charged contacts. The high frequency and strength, despite variation in structure and composition, of these π-interactions point to an important function in biological systems.

Structural insights into Aspergillus fumigatus lectin specificity: AFL binding sites are functionally non-equivalent

The Aspergillus fumigatus lectin AFL was recently described as a new member of the AAL lectin family. As a lectin from an opportunistic pathogen, it might play an important role in the interaction of the pathogen with the human host. A detailed study of structures of AFL complexed with several monosaccharides and oligosaccharides, including blood-group epitopes, was combined with affinity data from SPR and discussed in the context of previous findings. Its six binding sites are non-equivalent, and owing to minor differences in amino-acid composition they exhibit a marked difference in specific ligand recognition. AFL displays a high affinity in the micromolar range towards oligosaccharides which were detected in plants and also those bound on the human epithelia. All of these results indicate AFL to be a complex member of the lectin family and a challenging target for future medical research and, owing to its binding properties, a potentially useful tool in specific biotechnological applications.

PGluS: prediction of protein S-glutathionylation sites with multiple features and analysis

S-Glutathionylation is a reversible protein post-translational modification, which generates mixed disulfides between glutathione (GSH) and cysteine residues, playing an important role in regulating protein stability, activity, and redox regulation. To fully understand S-glutathionylation mechanisms, identification of substrates and specific S-glutathionylated sites is crucial. Compared with the labor-intensive and time-consuming experimental approaches, computational predictions of S-glutathionylated sites are very desirable due to their convenience and high speed. Therefore, in this study, a new bioinformatics tool named PGluS was developed to predict S-glutathionylated sites based on multiple features and support vector machines. The performance of PGluS was measured with an accuracy of 71.41% and a MCC of 0.431 using the 5-fold cross-validation on the training dataset. Additionally, PGluS was evaluated using an independent testing dataset resulting in an accuracy of 71.25%, which demonstrated that PGluS was very promising for predicting S-glutathionylated sites. Furthermore, feature analysis was performed and it was shown that all features adopted in this method contributed to the S-glutathionylation process. A site-specific analysis showed that S-glutathionylation was intimately correlated with the features derived from its surrounding sites. The conclusions derived from this study might help to understand more of the S-glutathionylation mechanism and guide the related experimental validation. For public access, PGluS is freely accessible at .

Serine and Cysteine π-Interactions in Nature: A Comparison of the Frequency, Structure, and Stability of Contacts Involving Oxygen and Sulfur

Despite many DNA–protein π-interactions in high-resolution crystal structures, only four X–H···π or X···π interactions were found between serine (Ser) or cysteine (Cys) and DNA nucleobase π-systems in over 100 DNA–protein complexes (where X = O for Ser and X = S for Cys). Nevertheless, 126 non-covalent contacts occur between Ser or Cys and the aromatic amino acids in many binding arrangements within proteins. Furthermore, Ser and Cys protein–protein π-interactions occur with similar frequencies and strengths. Most importantly, due to the great stability that can be provided to biological macromolecules (up to –20 kJ mol–1 for neutral π-systems or –40 kJ mol–1 for cationic π-systems), Ser and Cys π-interactions should be considered when analyzing protein stability and function.

DNA-protein π-interactions in nature: abundance, structure, composition and strength of contacts between aromatic amino acids and DNA nucleobases or deoxyribose sugar

Four hundred twenty-eight high-resolution DNA-protein complexes were chosen for a bioinformatics study. Although 164 crystal structures (38% of those searched) contained no interactions, 574 discrete π-contacts between the aromatic amino acids and the DNA nucleobases or deoxyribose were identified using strict criteria, including visual inspection. The abundance and structure of the interactions were determined by unequivocally classifying the contacts as either π-π stacking, π-π T-shaped or sugar-π contacts. Three hundred forty-four nucleobase-amino acid π-π contacts (60% of all interactions identified) were identified in 175 of the crystal structures searched. Unprecedented in the literature, 230 DNA-protein sugar-π contacts (40% of all interactions identified) were identified in 137 crystal structures, which involve C-H···π and/or lone-pair···π interactions, contain any amino acid and can be classified according to sugar atoms involved. Both π-π and sugar-π interactions display a range of relative monomer orientations and therefore interaction energies (up to -50 (-70) kJ mol(-1) for neutral (charged) interactions as determined using quantum chemical calculations). In general, DNA-protein π-interactions are more prevalent than perhaps currently accepted and the role of such interactions in many biological processes may yet to be uncovered.

Reduction of lectin valency drastically changes glycolipid dynamics in membranes but not surface avidity

Multivalency is proposed to play a role in the strong avidity of lectins for glycosylated cell surfaces and also in their ability to affect membrane dynamics by clustering glycosphingolipids. Lectins with modified valency were designed from the β-propeller fold of Ralstonia solanacearum lectin (RSL) that presents six fucose binding sites. After identification of key amino acids by molecular dynamics calculations, two mutants with reduced valency were produced. Isothermal titration calorimetry confirmed the loss of three high affinity binding sites for both mutants. Crystal structures indicated that residual low affinity binding occurred in W76A but not in R17A. The trivalent R17A mutant presented unchanged avidity toward fucosylated surfaces, when compared to hexavalent RSL. However, R17A is not able anymore to induce formation of membrane invaginations on giant unilamellar vesicules, indicating the crucial role of number of binding sites for clustering of glycolipids. In the human lung epithelial cell line H1299, wt-RSL is internalized within seconds whereas the kinetics of R17A uptake is largely delayed. Neolectins with tailored valency are promising tools to study membrane dynamics.

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.

Quantum Mechanics Approaches to Drug Research in the Era of Structural Chemogenomics

The rapid growth of the available crystallographic information about proteins and binding pockets creates remarkable opportunities for enriching the drug research pipelines with computational prediction of novel protein-ligand interactions. While ab initio quantum mechanical approaches are known to provide unprecedented accuracy in structure-based binding energy calculations, they are limited to only small systems of dozens of atoms. In the structural chemogenomics era, it is critical that new approaches are developed that enable application of QM methodologies to non-covalent interactions in systems as large as protein-ligand complexes and conformational ensembles. This perspective highlights recent advances towards bridging the gap between high accuracy and high volume computations in drug research.

A dynamic combinatorial approach for the analysis of weak carbohydrate/aromatic complexes: dissecting facial selectivity in CH/π stacking interactions

A dynamical combinatorial approach for the study of weak carbohydrate/aromatic interactions is presented. This methodology has been employed to dissect the subtle structure-stability relationships that govern facial selectivity in these supramolecular complexes.