Solvent structure improves docking prediction in lectin-carbohydrate complexes

Kinetic and dynamical properties of truncated hemoglobins of the Antarctic bacterium Pseudoalteromonas haloplanktis TAC125

Due to the low temperature, the Antarctic marine environment is challenging for protein functioning. Cold-adapted organisms have evolved proteins endowed with higher flexibility and lower stability in comparison to their thermophilic homologs, resulting in enhanced reaction rates at low temperatures. The Antarctic bacterium Pseudoalteromonas haloplanktis TAC125 (PhTAC125) genome is one of the few examples of coexistence of multiple hemoglobin genes encoding, among others, two constitutively transcribed 2/2 hemoglobins (2/2Hbs), also named truncated Hbs (TrHbs), belonging to the Group II (or O), annotated as PSHAa0030 and PSHAa2217. In this work, we describe the ligand binding kinetics and their interrelationship with the dynamical properties of globin Ph-2/2HbO-2217 by combining experimental and computational approaches and implementing a new computational method to retrieve information from molecular dynamic trajectories. We show that our approach allows us to identify docking sites within the protein matrix that are potentially able to transiently accommodate ligands and migration pathways connecting them. Consistently with ligand rebinding studies, our modeling suggests that the distal heme pocket is connected to the solvent through a low energy barrier, while inner cavities play only a minor role in modulating rebinding kinetics.

In silico discovery and anti-tumor bioactivities validation of an algal lectin from Kappaphycus alvarezii genome

Lectins are proteins that bind specifically and reversibly to carbohydrates, and some of them have significant anti-tumor activities. Compared to those of lectins from land plants, there are far fewer studies on algal lectins, despite of the high biodiversity of algae. However, canonical strategies based on chromatographic feature-oriented screening cannot satisfy the requirement for algal lectin discovery. In this study, prospecting for novel OAAH family lectins throughout 358 genomes of red algae and cyanobacteria was conducted. Then 35 candidate lectins and 1843 of their simulated mutated forms were virtually screened based on predicted binding specificities to characteristic carbohydrates on cancer cells inferred by a deep learning model. A new lectin, named Siye, was discovered in Kappaphycus alvarezii genome and further verified on different cancer cells. Without causing agglutination of erythrocytes, Siye showed significant cytotoxicity to four human cancer cell lines (IC50 values ranging from 0.11 to 3.95 μg/mL), including breast adenocarcinoma HCC1937, lung carcinoma A549, liver cancer HepG2 and romyelocytic leukemia HL60. And the cytotoxicity was induced through promoting apoptosis by regulating the caspase and the p53 pathway within 24 h. This study testifies the feasibility and efficiency of the genome mining guided by evolutionary theory and artificial intelligence in the discovery of algal lectins.

Unlocking Precision Docking for Metalloproteins

Metalloproteins play a fundamental role in molecular biology, contributing to various biological processes. However, the discovery of high-affinity ligands targeting metalloproteins has been delayed due, in part, to a lack of suitable tools and data. Molecular docking, a widely used technique for virtual screening of small-molecule ligand interactions with proteins, often faces challenges when applied to metalloproteins due to the particular nature of the ligand metal bond. To address these limitations associated with docking metalloproteins, we introduce a knowledge-driven docking approach known as "metalloprotein bias docking" (MBD), which extends the AutoDock Bias technique. We assembled a comprehensive data set of metalloprotein-ligand complexes from 15 different metalloprotein families, encompassing Ca, Co, Fe, Mg, Mn, and Zn metal ions. Subsequently, we conducted a performance analysis of our MBD method and compared it to the conventional docking (CD) program AutoDock4, applied to various metalloprotein targets within our data set. Our results demonstrate that MBD outperforms CD, significantly enhancing accuracy, selectivity, and precision in ligand pose prediction. Additionally, we observed a positive correlation between our predicted ligand free energies and the corresponding experimental values. These findings underscore the potential of MBD as a valuable tool for the effective exploration of metalloprotein-ligand interactions.

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.

Regulation of Intersubunit Interactions in Homotetramer of Glyceraldehyde-3-Phosphate Dehydrogenases upon Its Immobilization in Protein-Kappa-Carrageenan Gels

Polysaccharides, being biocompatible and biodegradable polymers, are highly attractive as materials for protein delivery systems. However, protein-polysaccharide interactions may lead to protein structural transformation. In the current study, we analyze the structural adjustment of a homotetrameric protein, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), upon its interactions with both flexible coil chain and the rigid helix of κ-carrageenan. FTIR spectroscopy was used to probe the secondary structures of both protein and polysaccharide. Electrostatically driven protein-polysaccharide interactions in dilute solutions resulted in an insoluble complex formation with a constant κ-carrageenan/GAPDH ratio of 0.2, which amounts to 75 disaccharide units per mole of protein tetramer. Upon interactions with both coiled and helical polysaccharides, a weakening of the intersubunit interactions was revealed and attributed to a partial GAPDH tetramer dissociation. In turn, protein distorted the helical conformation of κ-carrageenan when co-gelled. Molecular modeling showed the energy favorable interactions between κ-carrageenan and GAPDH at different levels of oligomerization. κ-Carrageenan binds in the region of the NAD-binding groove and the S-loop in OR contact, which may stabilize the OP dimers. The obtained results highlight the mutual conformational adjustment of oligomeric GAPDH and κ-carrageenan upon interaction and the stabilization of GAPDH's dissociated forms upon immobilization in polysaccharide gels.

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.

Biased Docking for Protein-Ligand Pose Prediction

The interaction between a protein and its ligands is one of the basic and most important processes in biological chemistry. Docking methods aim to predict the molecular 3D structure of protein-ligand complexes starting from coordinates of the protein and the ligand separately. They are widely used in both industry and academia, especially in the context of drug development projects. AutoDock4 is one of the most popular docking tools and, as for any docking method, its performance is highly system dependent. Knowledge about specific protein-ligand interactions on a particular target can be used to successfully overcome this limitation. Here, we describe how to apply the AutoDock Bias protocol, a simple and elegant strategy that allows users to incorporate target-specific information through a modified scoring function that biases the ligand structure towards those poses (or conformations) that establish selected interactions. We discuss two examples using different bias sources. In the first, we show how to steer dockings towards interactions derived from crystal structures of the receptor with different ligands; in the second example, we define and apply hydrophobic biases derived from Molecular Dynamics simulations in mixed solvents. Finally, we discuss general concepts of biased docking, its performance in pose prediction, and virtual screening campaigns as well as other potential applications.

Structural insights in interactions between RNase from Bacillus Intermedius and rhamnogalacturonan I from potato

Being biocompatible and biodegradable polymers, polysaccharides present a perspective material for drug delivery systems. This study aimed at unraveling the molecular details of interactions between rhamnogalacturonan I, brunched with galactan side chains, and RNase from Bacillus Intermedius, binase. FTIR- and NMR-spectroscopic analyses showed that binase interacts with side chains of the polysaccharide. In complexes with polysaccharide, the protein retains its native structure. The 2D-NMR techniques revealed eight protein residues responsive to polysaccharide binding. Further, computer simulations were carried out to provide the atomistic details of binase-polysaccharide complexes. Both blind and knowledge-based docking procedures elucidate the existence of epitopes on the binase surface with the preferential binding of galactan fragments. The refinement of these complexes by molecular dynamics simulations confirmed stable protein-polysaccharide interactions. The results of this study strengthen the knowledge on non-specific protein-carbohydrate interactions and outline the rhamnogalacturonan I as a possible matrix material for protein delivery systems.

Carbohydrate-Protein Interactions: Advances and Challenges

A carbohydrate, also called saccharide in biochemistry, is a biomolecule consisting of carbon (C), hydrogen (H) and oxygen (O) atoms. For example, sugars are low molecular-weight carbohydrates, and starches are high molecular-weight carbohydrates. Carbohydrates are the most abundant organic substances in nature and essential constituents of all living things. Protein-carbohydrate interactions play important roles in many biological processes, such as cell growth, differentiation, and aggregation. They also have broad applications in pharmaceutical drug design. In this review, we will summarize the characteristic features of protein-carbohydrate interactions and review the computational methods for structure prediction, energy calculations, and kinetic studies of protein-carbohydrate complexes. Finally, we will discuss the challenges in this field.

Prediction of protein-carbohydrate complex binding affinity using structural features

Protein-carbohydrate interactions play a major role in several cellular and biological processes. Elucidating the factors influencing the binding affinity of protein-carbohydrate complexes and predicting their free energy of binding provide deep insights for understanding the recognition mechanism. In this work, we have collected the experimental binding affinity data for a set of 389 protein-carbohydrate complexes and derived several structure-based features such as contact potentials, interaction energy, number of binding residues and contacts between different types of atoms. Our analysis on the relationship between binding affinity and structural features revealed that the important factors depend on the type of the complex based on number of carbohydrate and protein chains. Specifically, binding site residues, accessible surface area, interactions between various atoms and energy contributions are important to understand the binding affinity. Further, we have developed multiple regression equations for predicting the binding affinity of protein-carbohydrate complexes belonging to six categories of protein-carbohydrate complexes. Our method showed an average correlation and mean absolute error of 0.731 and 1.149 kcal/mol, respectively, between experimental and predicted binding affinities on a jackknife test. We have developed a web server PCA-Pred, Protein-Carbohydrate Affinity Predictor, for predicting the binding affinity of protein-carbohydrate complexes. The web server is freely accessible at https://web.iitm.ac.in/bioinfo2/pcapred/. The web server is implemented using HTML and Python and supports recent versions of major browsers such as Chrome, Firefox, IE10 and Opera.

AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions

SUMMARY

The performance of docking calculations can be improved by tuning parameters for the system of interest, e.g. biasing the results towards the formation of relevant protein-ligand interactions, such as known ligand pharmacophore or interaction sites derived from cosolvent molecular dynamics. AutoDock Bias is a straightforward and easy to use script-based method that allows the introduction of different types of user-defined biases for fine-tuning AutoDock4 docking calculations.

AVAILABILITY AND IMPLEMENTATION

AutoDock Bias is distributed with MGLTools (since version 1.5.7), and freely available on the web at http://ccsb.scripps.edu/mgltools/ or http://autodockbias.wordpress.com.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Structural Biology of Galectin-Ligand Recognition: Current Advances in Modeling Tools, Protein Engineering, and Inhibitor Design

Galectins (formerly known as “S-type lectins”) are a subfamily of soluble proteins that typically bind β-galactoside carbohydrates with high specificity. They are present in many forms of life, from nematodes and fungi to animals, where they perform a wide range of functions. Particularly in humans, different types of galectins have been described differing not only in their tissue expression but also in their cellular location, oligomerization, fold architecture and carbohydrate-binding affinity. This distinct yet sometimes overlapping distributions and physicochemical attributes make them responsible for a wide variety of both intra- and extracellular functions, including tremendous importance in immunity and disease. In this review, we aim to provide a general description of galectins most important structural features, with a special focus on the molecular determinants of their carbohydrate-recognition ability. For that purpose, we structurally compare the human galectins, in light of recent mutagenesis studies and novel X-ray structures. We also offer a detailed description on how to use the solvent structure surrounding the protein as a tool to get better predictions of galectin-carbohydrate complexes, with a potential application to the rational design of glycomimetic inhibitory compounds. Finally, using Gal-1 and Gal-3 as paramount examples, we review a series of recent advances in the development of engineered galectins and galectin inhibitors, aiming to dissect the structure-activity relationship through the description of their interaction at the molecular level.

Computational Insight Into the Small Molecule Intervening PD-L1 Dimerization and the Potential Structure-Activity Relationship

Recently, small-molecule compounds have been reported to block the PD-1/PD-L1 interaction by inducing the dimerization of PD-L1. All these inhibitors had a common scaffold and interacted with the cavity formed by two PD-L1 monomers. This special interactive mode provided clues for the structure-based drug design, however, also showed limitations for the discovery of small-molecule inhibitors with new scaffolds. In this study, we revealed the structure-activity relationship of the current small-molecule inhibitors targeting dimerization of PD-L1 by predicting their binding and unbinding mechanism via conventional molecular dynamics and metadynamics simulation. During the binding process, the representative inhibitors (BMS-8 and BMS-1166) tended to have a more stable binding mode with one PD-L1 monomer than the other and the small-molecule inducing PD-L1 dimerization was further stabilized by the non-polar interaction of Ile54, Tyr56, Met115, Ala121, and Tyr123 on both monomers and the water bridges involved in ALys124. The unbinding process prediction showed that the PD-L1 dimerization kept stable upon the dissociation of ligands. It's indicated that the formation and stability of the small-molecule inducing PD-L1 dimerization was the key factor for the inhibitory activities of these ligands. The contact analysis, R-group based quantitative structure-activity relationship (QSAR) analysis and molecular docking further suggested that each attachment point on the core scaffold of ligands had a specific preference for pharmacophore elements when improving the inhibitory activities by structural modifications. Taken together, the results in this study could guide the structural optimization and the further discovery of novel small-molecule inhibitors targeting PD-L1.

The role of hydration effects in 5-fluorouridine binding to SOD1: insight from a new 3D-RISM-KH based protocol for including structural water in docking simulations

Misfolded Cu/Zn superoxide dismutase enzyme (SOD1) shows prion-like propagation in neuronal cells leading to neurotoxic aggregates that are implicated in amyotrophic lateral sclerosis (ALS). Tryptophan-32 (W32) in SOD1 is part of a potential site for templated conversion of wild type SOD1. This W32 binding site is located on a convex, solvent exposed surface of the SOD1 suggesting that hydration effects can play an important role in ligand recognition and binding. A recent X-ray crystal structure has revealed that 5-Fluorouridine (5-FUrd) binds at the W32 binding site and can act as a pharmacophore scaffold for the development of anti-ALS drugs. In this study, a new protocol is developed to account for structural (non-displaceable) water molecules in docking simulations and successfully applied to predict the correct docked conformation binding modes of 5-FUrd at the W32 binding site. The docked configuration is within 0.58 Å (RMSD) of the observed configuration. The docking protocol involved calculating a hydration structure around SOD1 using molecular theory of solvation (3D-RISM-KH, 3D-Reference Interaction Site Model-Kovalenko-Hirata) whereby, non-displaceable water molecules are identified for docking simulations. This protocol was also used to analyze the hydrated structure of the W32 binding site and to explain the role of solvation in ligand recognition and binding to SOD1. Structural water molecules mediate hydrogen bonds between 5-FUrd and the receptor, and create an environment favoring optimal placement of 5-FUrd in the W32 binding site.

An efficient use of X-ray information, homology modeling, molecular dynamics and knowledge-based docking techniques to predict protein-monosaccharide complexes

Unraveling the structure of lectin-carbohydrate complexes is vital for understanding key biological recognition processes and development of glycomimetic drugs. Molecular Docking application to predict them is challenging due to their low affinity, hydrophilic nature and ligand conformational diversity. In the last decade several strategies, such as the inclusion of glycan conformation specific scoring functions or our developed solvent-site biased method, have improved carbohydrate docking performance but significant challenges remain, in particular, those related to receptor conformational diversity. In the present work we have analyzed conventional and solvent-site biased autodock4 performance concerning receptor conformational diversity as derived from different crystal structures (apo and holo), Molecular Dynamics snapshots and Homology-based models, for 14 different lectin-monosaccharide complexes. Our results show that both conventional and biased docking yield accurate lectin-monosaccharide complexes, starting from either apo or homology-based structures, even when only moderate (45%) sequence identity templates are available. An essential element for success is a proper combination of a middle-sized (10-100 structures) conformational ensemble, derived either from Molecular dynamics or multiple homology model building. Consistent with our previous works, results show that solvent-site biased methods improve overall performance, but that results are still highly system dependent. Finally, our results also show that docking can select the correct receptor structure within the ensemble, underscoring the relevance of joint evaluation of both ligand pose and receptor conformation.

Calcium-Binding Generates the Semi-Clathrate Waters on a Type II Antifreeze Protein to Adsorb onto an Ice Crystal Surface

Hydration is crucial for a function and a ligand recognition of a protein. The hydration shell constructed on an antifreeze protein (AFP) contains many organized waters, through which AFP is thought to bind to specific ice crystal planes. For a Ca²⁺-dependent species of AFP, however, it has not been clarified how 1 mol of Ca²⁺-binding is related with the hydration and the ice-binding ability. Here we determined the X-ray crystal structure of a Ca²⁺-dependent AFP (jsAFP) from Japanese smelt, Hypomesus nipponensis, in both Ca²⁺-bound and -free states. Their overall structures were closely similar (Root mean square deviation (RMSD) of Cα = 0.31 Å), while they exhibited a significant difference around their Ca²⁺-binding site. Firstly, the side-chains of four of the five Ca²⁺-binding residues (Q92, D94 E99, D113, and D114) were oriented to be suitable for ice binding only in the Ca²⁺-bound state. Second, a Ca²⁺-binding loop consisting of a segment D94–E99 becomes less flexible by the Ca²⁺-binding. Third, the Ca²⁺-binding induces a generation of ice-like clathrate waters around the Ca²⁺-binding site, which show a perfect position-match to the waters constructing the first prism plane of a single ice crystal. These results suggest that generation of ice-like clathrate waters induced by Ca²⁺-binding enables the ice-binding of this protein.

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.

Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking

In this work, we developed a computational protocol that employs multiple molecular docking experiments, followed by pose clustering, molecular dynamic simulations (10 ns), and energy rescoring to produce reliable 3D models of antibody-carbohydrate complexes. The protocol was applied to 10 antibody-carbohydrate co-complexes and three unliganded (apo) antibodies. Pose clustering significantly reduced the number of potential poses. For each system, 15 or fewer clusters out of 100 initial poses were generated and chosen for further analysis. Molecular dynamics (MD) simulations allowed the docked poses to either converge or disperse, and rescoring increased the likelihood that the best-ranked pose was an acceptable pose. This approach is amenable to automation and can be a valuable aid in determining the structure of antibody-carbohydrate complexes provided there is no major side chain rearrangement or backbone conformational change in the H3 loop of the CDR regions. Further, the basic protocol of docking a small ligand to a known binding site, clustering the results, and performing MD with a suitable force field is applicable to any protein ligand system.

Synthesis of β-galactosylamides as ligands of the peanut lectin. Insights into the recognition process

The synthesis of mono and divalent β-galactosylamides linked to a hydroxylated chain having a C2 symmetry axis derived from l-tartaric anhydride is reported. Reference compounds devoid of hydroxyl groups in the linker were also prepared from β-galactosylamine and succinic anhydride. After functionalization with an alkynyl residue, the resulting building blocks were grafted onto different azide-equipped scaffolds through the copper catalyzed azide-alkyne cycloaddition. Thus, a family of structurally related mono and divalent β-N-galactopyranosylamides was obtained and fully characterized. The binding affinities of the ligands towards the model lectin PNA were measured by the enzyme-linked lectin assay (ELLA). The IC₅₀ values were significantly higher than that of galactose but the presence of hydroxyl groups in the aglycone chain improved lectin recognition. Docking and molecular dynamics experiments were in accordance with the hypothesis that a hydroxyl group properly disposed in the linker could mimic the Glc O3 in the recognition process. On the other hand, divalent presentation of the ligands led to lectin affinity enhancements.

Theoretical Insights into the Reaction and Inhibition Mechanism of Metal-Independent Retaining Glycosyltransferase Responsible for Mycothiol Biosynthesis

Understanding enzymatic reactions with atomic resolution has proven in recent years to be of tremendous interest for biochemical research, and thus, the use of QM/MM methods for the study of reaction mechanisms is experiencing a continuous growth. Glycosyltransferases (GTs) catalyze the formation of glycosidic bonds, and are important for many biotechnological purposes, including drug targeting. Their reaction product may result with only one of the two possible stereochemical outcomes for the reacting anomeric center, and therefore, they are classified as either inverting or retaining GTs. While the inverting GT reaction mechanism has been widely studied, the retaining GT mechanism has always been controversial and several questions remain open to this day. In this work, we take advantage of our recent GPU implementation of a pure QM(DFT-PBE)/MM approach to explore the reaction and inhibition mechanism of MshA, a key retaining GT responsible for the first step of mycothiol biosynthesis, a low weight thiol compound found in pathogens like Mycobacterium tuberculosis that is essential for its survival under oxidative stress conditions. Our results show that the reaction proceeds via a front-side S_Ni-like concerted reaction mechanism (D_NA_N in IUPAC nomenclature) and has a 17.5 kcal/mol free energy barrier, which is in remarkable agreement with experimental data. Detailed analysis shows that the key reaction step is the diphosphate leaving group dissociation, leading to an oxocarbenium-ion-like transition state. In contrast, fluorinated substrate analogues increase the reaction barrier significantly, rendering the enzyme effectively inactive. Detailed analysis of the electronic structure along the reaction suggests that this particular inhibition mechanism is associated with fluorine's high electronegative nature, which hinders phosphate release and proper stabilization of the transition state.

Impact of human galectin-1 binding to saccharide ligands on dimer dissociation kinetics and structure

Endogenous lectins can control critical biological responses, including cell communication, signaling, angiogenesis and immunity by decoding glycan-containing information on a variety of cellular receptors and the extracellular matrix. Galectin-1 (Gal-1), a prototype member of the galectin family, displays only one carbohydrate recognition domain and occurs in a subtle homodimerization equilibrium at physiologic concentrations. Such equilibrium critically governs the function of this lectin signaling by allowing tunable interactions with a preferential set of glycosylated receptors. Here, we used a combination of experimental and computational approaches to analyze the kinetics and mechanisms connecting Gal-1 ligand unbinding and dimer dissociation processes. Kinetic constants of both processes were found to differ by an order of magnitude. By means of steered molecular dynamics simulations, the ligand unbinding process was followed monitoring water occupancy changes. By determining the water sites in a carbohydrate binding place during the unbinding process, we found that rupture of ligand-protein interactions induces an increase in energy barrier while ligand unbinding process takes place, whereas the entry of water molecules to the binding groove and further occupation of their corresponding water sites contributes to lowering of the energy barrier. Moreover, our findings suggested local asymmetries between the two subunits in the dimer structure detected at a nanosecond timescale. Thus, integration of experimental and computational data allowed a more complete understanding of lectin ligand binding and dimerization processes, suggesting new insights into the relationship between Gal-1 structure and function and renewing the discussion on the biophysics and biochemistry of lectin-ligand lattices.

Binding of the substrate UDP-glucuronic acid induces conformational changes in the xanthan gum glucuronosyltransferase

GumK is a membrane-associated glucuronosyltransferase of Xanthomonas campestris that is involved in xanthan gum biosynthesis. GumK belongs to the inverting GT-B superfamily and catalyzes the transfer of a glucuronic acid (GlcA) residue from uridine diphosphate (UDP)-GlcA (UDP-GlcA) to a lipid-PP-trisaccharide embedded in the membrane of the bacteria. The structure of GumK was previously described in its apo- and UDP-bound forms, with no significant conformational differences being observed. Here, we study the behavior of GumK toward its donor substrate UDP-GlcA. Turbidity measurements revealed that the interaction of GumK with UDP-GlcA produces aggregation of protein molecules under specific conditions. Moreover, limited proteolysis assays demonstrated protection of enzymatic digestion when UDP-GlcA is present, and this protection is promoted by substrate binding. Circular dichroism spectroscopy also revealed changes in the GumK tertiary structure after UDP-GlcA addition. According to the obtained emission fluorescence results, we suggest the possibility of exposure of hydrophobic residues upon UDP-GlcA binding. We present in silico-built models of GumK complexed with UDP-GlcA as well as its analogs UDP-glucose and UDP-galacturonic acid. Through molecular dynamics simulations, we also show that a relative movement between the domains appears to be specific and to be triggered by UDP-GlcA. The results presented here strongly suggest that GumK undergoes a conformational change upon donor substrate binding, likely bringing the two Rossmann fold domains closer together and triggering a change in the N-terminal domain, with consequent generation of the acceptor substrate binding site.

Vina-Carb: Improving Glycosidic Angles during Carbohydrate Docking

Molecular docking programs are primarily designed to align rigid, drug-like fragments into the binding sites of macromolecules and frequently display poor performance when applied to flexible carbohydrate molecules. A critical source of flexibility within an oligosaccharide is the glycosidic linkages. Recently, Carbohydrate Intrinsic (CHI) energy functions were reported that attempt to quantify the glycosidic torsion angle preferences. In the present work, the CHI-energy functions have been incorporated into the AutoDock Vina (ADV) scoring function, subsequently termed Vina-Carb (VC). Two user-adjustable parameters have been introduced, namely, a CHI- energy weight term (chi_coeff) that affects the magnitude of the CHI-energy penalty and a CHI-cutoff term (chi_cutoff) that negates CHI-energy penalties below a specified value. A data set consisting of 101 protein-carbohydrate complexes and 29 apoprotein structures was used in the development and testing of VC, including antibodies, lectins, and carbohydrate binding modules. Accounting for the intramolecular energies of the glycosidic linkages in the oligosaccharides during docking led VC to produce acceptable structures within the top five ranked poses in 74% of the systems tested, compared to a success rate of 55% for ADV. An enzyme system was employed in order to illustrate the potential application of VC to proteins that may distort glycosidic linkages of carbohydrate ligands upon binding. VC represents a significant step toward accurately predicting the structures of protein-carbohydrate complexes. Furthermore, the described approach is conceptually applicable to any class of ligands that populate well-defined conformational states.

WATCLUST: a tool for improving the design of drugs based on protein-water interactions

MOTIVATION

Water molecules are key players for protein folding and function. On the protein surface, water is not placed randomly, but display instead a particular structure evidenced by the presence of specific water sites (WS). These WS can be derived and characterized using explicit water Molecular Dynamics simulations, providing useful information for ligand binding prediction and design. Here we present WATCLUST, a WS determination and analysis tool running on the VMD platform. The tool also allows direct transfer of the WS information to Autodock program to perform biased docking.

AVAILABILITY AND IMPLEMENTATION

The WATCLUST plugin and documentation are freely available at http://sbg.qb.fcen.uba.ar/watclust/.

CONTACT

marcelo@qi.fcen.uba.ar, adrian@qi.fcen.uba.ar.

Thermodynamics of binding of di- and tetrasubstituted naphthalene diimide ligands to DNA G-quadruplex

Naphthalene diimide ligands have the potential to stabilize human telomeric G-quadruplex DNA via noncovalent interactions. Stabilization of G-quadruplex high order structures has become an important strategy to develop novel anticancer therapeutics. In this study four naphthalene diimide based ligands were analyzed in order to elucidate the principal factors determining contributions to G-quadruplex-ligand binding. Three possible modes of binding and their respective Gibbs free energies for two naphthalene diimide based di-N-alkylpyridinium substituted ligands have been determined using a molecular docking technique and compared to experimental results. The structures obtained from the molecular docking calculations, were analyzed using the ab initio based fragment molecular orbital (FMO) method in order to determine the major enthalpic contributions to the binding and types of interactions between the ligand and specific residues of the G-quadruplex. A computational methodology for the efficient and inexpensive ligand optimization as compared to fully ab initio methods based on the estimation of binding affinities of the naphthalene diimide derived ligands to G-quadruplex is proposed.

Role of water in ligand binding to maltose-binding protein: insight from a new docking protocol based on the 3D-RISM-KH molecular theory of solvation

Maltose-binding protein is a periplasmic binding protein responsible for transport of maltooligosaccarides through the periplasmic space of Gram-negative bacteria, as a part of the ABC transport system. The molecular mechanisms of the initial ligand binding and induced large scale motion of the protein's domains still remain elusive. In this study, we use a new docking protocol that combines a recently proposed explicit water placement algorithm based on the 3D-RISM-KH molecular theory of solvation and conventional docking software (AutoDock Vina) to explain the mechanisms of maltotriose binding to the apo-open state of a maltose-binding protein. We confirm the predictions of previous NMR spectroscopic experiments on binding modes of the ligand. We provide the molecular details on the binding mode that was not previously observed in the X-ray experiments. We show that this mode, which is defined by the fine balance between the protein-ligand direct interactions and solvation effects, can trigger the protein's domain motion resulting in the holo-closed structure of the maltose-binding protein with the maltotriose ligand in excellent agreement with the experimental data. We also discuss the role of water in blocking unfavorable binding sites and water-mediated interactions contributing to the stability of observable binding modes of maltotriose.

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.