118 research outputs found

    SuperSweet—a resource on natural and artificial sweetening agents

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    A vast number of sweet tasting molecules are known, encompassing small compounds, carbohydrates, d-amino acids and large proteins. Carbohydrates play a particularly big role in human diet. The replacement of sugars in food with artificial sweeteners is common and is a general approach to prevent cavities, obesity and associated diseases such as diabetes and hyperlipidemia. Knowledge about the molecular basis of taste may reveal new strategies to overcome diet-induced diseases. In this context, the design of safe, low-calorie sweeteners is particularly important. Here, we provide a comprehensive collection of carbohydrates, artificial sweeteners and other sweet tasting agents like proteins and peptides. Additionally, structural information and properties such as number of calories, therapeutic annotations and a sweetness-index are stored in SuperSweet. Currently, the database consists of more than 8000 sweet molecules. Moreover, the database provides a modeled 3D structure of the sweet taste receptor and binding poses of the small sweet molecules. These binding poses provide hints for the design of new sweeteners. A user-friendly graphical interface allows similarity searching, visualization of docked sweeteners into the receptor etc. A sweetener classification tree and browsing features allow quick requests to be made to the database. The database is freely available at: http://bioinformatics.charite.de/sweet/

    Design, Synthesis, and Structure−Activity Relationship Exploration of 1-Substituted 4-Aroyl-3-hydroxy-5-phenyl-1H-pyrrol-2(5H)-one Analogues as Inhibitors of the Annexin A2−S100A10 Protein Interaction

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    This research was supported by grants from Cancer Research UK. H.K.M. was funded by a Biotechnology and Biological Sciences Research Council studentship.S100 proteins are small adaptors that regulate the activity of partner proteins by virtue of direct protein interactions. Here, we describe the first small molecule blockers of the interaction between S100A10 and annexin A2. Molecular docking yielded candidate blockers that were screened for competition of the binding of an annexin A2 peptide to S100A10. Several inhibitory clusters were identified with some containing compounds with potency in the lower micromolar range. We chose 3-hydroxy-1-(2-hydroxypropyl)-5-(4-isopropylphenyl)-4-(4-methylbenzoyl)-1H-pyrrol-2(5H)-one (1a) as a starting point for structure-activity studies. These confirmed the hypothetical binding mode from the virtual screen for this series of molecules. Selected compounds disrupted the physiological complex of annexin A2 and S100A10, both in a broken cell preparation and inside MDA-MB-231 breast cancer cells. Thus, this class of compounds has promising properties as inhibitors of the interaction between annexin A2 and S100A10 and may help to elucidate the cellular function of this protein interaction.Peer reviewe

    Automated Docking Screens: A Feasibility Study

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    Molecular docking is themost practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCKBlaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCKBlaster recapitulates the crystal ligand pose within 2 A ̊ rmsd 50-60 % of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5 % of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5 % of 100 property-matched decoys while also posing within 2 A ̊ rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available a

    Comparative 3D QSAR study on β1-, β2-, and β3-adrenoceptor agonists

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    A quantitative structure–activity relationship study of tryptamine-based derivatives of β1-, β2-, and β3-adrenoceptor agonists was conducted using comparative molecular field analysis (CoMFA). Correlation coefficients (cross-validated r2) of 0.578, 0.595, and 0.558 were obtained for the three subtypes, respectively, in three different CoMFA models. All three CoMFA models have different steric and electrostatic contributions, implying different requirements inside the binding cavity. The CoMFA coefficient contour plots of the three models and comparisons among these plots provide clues regarding the main chemical features responsible for the biological activity variations and also result in predictions which correlate very well with the observed biological activity. Based on the analysis, a summary regeospecific description of the requirements for improving β-adrenoceptor subtype selectivity is given
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