AutoMap: A tool for analyzing protein–ligand recognition using multiple ligand binding modes

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.

Identification of G protein-coupled receptor 55 (GPR55) as a target of curcumin

The identification of molecular targets of bioactive food components is important to understand the mechanistic aspect of their physiological functions. Here, we have developed a screening system that enables us to determine the activation of G protein-coupled receptors (GPCRs) by food components and have identified GPR55 as a target for curcumin. Curcumin activated GPR55 and induced serum-response element- and serum-response factor-mediated transcription, which were inhibited by Rho kinase and GPR55 antagonists. Both the methoxy group and the heptadienone moiety of curcumin were required for GPR55 activation. The F190^5.47 residue of GPR55 was important for the interaction with curcumin. The curcumin-induced secretion of glucagon-like peptide-1 in GLUTag cells was inhibited by a GPR55 antagonist. These results indicate that expression screening is a useful system to identify GPCRs as targets of food components and strongly suggest that curcumin activates GPR55 as an agonist, which is involved in the physiological function of curcumin.

Comprehensive analysis of carbohydrate-protein recognition in the Protein Data Bank

Carbohydrate-protein interactions underpin wide-ranging aspects of biology. However, such interactions remain relatively unexplored in pharmaceutical and biotechnological applications, in part due to the challenges associated with their structural characterisation, both experimentally and computationally. Knowledge-based approaches have shown great success in the prediction of drug-protein and protein-protein interactions, although have not been comprehensively investigated for carbohydrate-protein interactions. In this work, carbohydrate-protein complexes from the Protein Data Bank were comprehensively obtained and analysed to identify patterns in how carbohydrate-protein interactions are mediated.

Assessment of malathion toxicity on cytophysiological activity, DNA damage and antioxidant enzymes in root of Allium cepa model

The current study was emphasized to assess the effect of malathion on root system (cell division and kinetics of the root elongation) and stress related parameters in Allium cepa L. The roots were exposed to different concentrations (0.05, 0.13, 0.26, 0.39 and 0.52 g/L) of malathion for different treatment periods (4, 8 and 18 h). The results revealed that malathion application affected the growth rate and cell division in root tips. The root elongation kinetics were impaired at 0.13 to 0.52 g/L concentrations. Reduction in tissue water content (TWC) indicated the limited osmotic adjustment due to membrane damage. Further, a decrease in sucrose content was observed in contrast to the accumulation of proline (upto 0.39 g/L). Moreover, malathion exposure elevated the levels of lipid peroxidation followed by changes in antioxidant enzymes status. The activities of ascorbate peroxidase (APX) and glutathione reductase (GR) were down-regulated whereas the activities of catalase (CAT), glutathione-S-transferase (GST) and superoxide dismutase (SOD) were up-regulated except in 0.52 g/L malathion. The molecular docking study of malathion with CAT, GST, SOD, APX and GR also supported of above results for their activity. All these physiological responses varied with increasing malathion concentration and duration of treatment. The single cell gel electrophoresis results showed that all concentrations of malathion induced DNA damage in root cells. The findings depicted that malathion application induces cytotoxic and phytotoxic effects mediated through oxidative stress and subsequent injuries.

Wnt Binding Affinity Prediction for Putative Frizzled-Type Cysteine-Rich Domains

Several proteins other than the frizzled receptors (Fzd) and the secreted Frizzled-related proteins (sFRP) contain Fzd-type cysteine-rich domains (CRD). We have termed these domains “putative Fzd-type CRDs”, as the relevance of Wnt signalling in the majority of these is unknown; the RORs, an exception to this, are well known for mediating non-canonical Wnt signalling. In this study, we have predicted the likely binding affinity of all Wnts for all putative Fzd-type CRDs. We applied both our previously determined Wnt‒Fzd CRD binding affinity prediction model, as well as a newly devised model wherein the lipid term was forced to contribute favourably to the predicted binding energy. The results obtained from our new model indicate that certain putative Fzd CRDs are much more likely to bind Wnts, in some cases exhibiting selectivity for specific Wnts. The results of this study inform the investigation of Wnt signalling modulation beyond Fzds and sFRPs.

Modeling large protein-glycosaminoglycan complexes using a fragment-based approach

Glycosaminoglycans (GAGs), a major constituent of the extracellular matrix, participate in cell-signaling by binding specific proteins. Structural data on protein-GAG interactions are crucial to understand and modulate these signaling processes, with potential applications in regenerative medicine. However, experimental and theoretical approaches used to study GAG-protein systems are challenged by GAGs high flexibility limiting the conformational sampling above a certain size, and by the scarcity of GAG-specific docking tools compared to protein-protein or protein-drug docking approaches. We present for the first time an automated fragment-based method for docking GAGs on a protein binding site. In this approach, trimeric GAG fragments are flexibly docked to the protein, assembled based on their spacial overlap, and refined by molecular dynamics. The method appeared more successful than the classical full-ligand approach for most of 13 tested complexes with known structure. The approach is particularly promising for docking of long GAG chains, which represents a bottleneck for classical docking approaches applied to these systems. © 2019 Wiley Periodicals, Inc.

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.

Antibody-Carbohydrate Recognition from Docked Ensembles Using the AutoMap Procedure

Carbohydrate-protein recognition is vital to many processes in health and disease. In particular, elucidation of the structural basis of carbohydrate binding is important to the development of oligosaccharides and oligosaccharide mimetics as vaccines for infectious diseases and cancer. Computational structural techniques are valuable for the study of carbohydrate-protein recognition due to the challenges associated with experimental determination of carbohydrate-protein complexes. AutoMap is a computer program that we have developed to study protein-ligand recognition. AutoMap determines the interactions taking place in a set of highly ranked poses obtained from molecular docking and processes these to identify the protein residues most likely to be involved in interactions. In this protocol, we describe the use of AutoMap and illustrate its suitability for studying antibody recognition of the Lewis Y tetrasaccharide, which is a potential cancer vaccine antigen.

A Simple Method for Discovering Druggable, Specific Glycosaminoglycan-Protein Systems. Elucidation of Key Principles from Heparin/Heparan Sulfate-Binding Proteins

Glycosaminoglycans (GAGs) affect human physiology and pathology by modulating more than 500 proteins. GAG-protein interactions are generally assumed to be ionic and nonspecific, but specific interactions do exist. Here, we present a simple method to identify the GAG-binding site (GBS) on proteins that in turn helps predict high specific GAG-protein systems. Contrary to contemporary thinking, we found that the electrostatic potential at basic arginine and lysine residues neither identifies the GBS consistently, nor its specificity. GBSs are better identified by considering the potential at neutral hydrogen bond donors such as asparagine or glutamine sidechains. Our studies also reveal that an unusual constellation of ionic and non-ionic residues in the binding site leads to specificity. Nature engineers the local environment of Asn45 of antithrombin, Gln255 of 3-O-sulfotransferase 3, Gln163 and Asn167 of 3-O-sulfotransferase 1 and Asn27 of basic fibroblast growth factor in the respective GBSs to induce specificity. Such residues are distinct from other uncharged residues on the same protein structure in possessing a significantly higher electrostatic potential, resultant from the local topology. In contrast, uncharged residues on nonspecific GBSs such as thrombin and serum albumin possess a diffuse spread of electrostatic potential. Our findings also contradict the paradigm that GAG-binding sites are simply a collection of contiguous Arg/Lys residues. Our work demonstrates the basis for discovering specifically interacting and druggable GAG-protein systems based on the structure of protein alone, without requiring access to any structure-function relationship data.

Improvements, trends, and new ideas in molecular docking: 2012-2013 in review

Molecular docking is a computational method for predicting the placement of ligands in the binding sites of their receptor(s). In this review, we discuss the methodological developments that occurred in the docking field in 2012 and 2013, with a particular focus on the more difficult aspects of this computational discipline. The main challenges and therefore focal points for developments in docking, covered in this review, are receptor flexibility, solvation, scoring, and virtual screening. We specifically deal with such aspects of molecular docking and its applications as selection criteria for constructing receptor ensembles, target dependence of scoring functions, integration of higher-level theory into scoring, implicit and explicit handling of solvation in the binding process, and comparison and evaluation of docking and scoring methods.

Study on the interaction of catalase with pesticides by flow injection chemiluminescence and molecular docking

The interaction mechanisms of catalase (CAT) with pesticides (including organophosphates: disulfoton, isofenphos-methyl, malathion, isocarbophos, dimethoate, dipterex, methamidophos and acephate; carbamates: carbaryl and methomyl; pyrethroids: fenvalerate and deltamethrin) were first investigated by flow injection (FI) chemiluminescence (CL) analysis and molecular docking. By homemade FI-CL model of lg[(I0-I)/I]=lgK+nlg[D], it was found that the binding processes of pesticides to CAT were spontaneous with the apparent binding constants K of 10(3)-10(5) L mol(-1) and the numbers of binding sites about 1.0. The binding abilities of pesticides to CAT followed the order: fenvalerate>deltamethrin>disulfoton>isofenphos-methyl>carbaryl>malathion>isocarbophos>dimethoate>dipterex>acephate>methomyl>methamidophos, which was generally similar to the order of determination sensitivity of pesticides. The thermodynamic parameters revealed that CAT bound with hydrophobic pesticides by hydrophobic interaction force, and with hydrophilic pesticides by hydrogen bond and van der Waals force. The pesticides to CAT molecular docking study showed that pesticides could enter into the cavity locating among the four subdomains of CAT, giving the specific amino acid residues and hydrogen bonds involved in CAT-pesticides interaction. It was also found that the lgK values of pesticides to CAT increased regularly with increasing lgP, Mr, MR and MV, suggesting that the hydrophobicity and steric property of pesticide played essential roles in its binding to CAT.