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Drug metabolism, toxicity, and their interaction profiles are major issues in the drug-discovery and lead-optimization processes. The cytochromes P450 (CYPs) 2D6 and 2C9 are enzymes involved in the oxidative metabolism of a majority of marketed drugs. Therefore, the prediction of the binding affinity towards CYP2D6 and CYP2C9 would be beneficial for identifying cytochrome-mediated adverse effects triggered by drugs or chemicals (e.g., toxic reactions, drug-drug, and food-drug interactions). By identifying the binding mode by using pharmacophore prealignment, automated flexible docking, and by quantifying the binding affinity by multidimensional QSAR (mQSAR), we validated a model family of 56 compounds (46 training, 10 test) and 85 compounds (68 training, 17 test) for CYP2D6 and CYP2C9, respectively. The correlation with the experimental data (cross-validated r²=0.811 for CYP2D6 and 0.687 for CYP2C9) suggests that our approach is suited for predicting the binding affinity of compounds towards CYP2D6 and CYP2C9. The models were challenged by Y-scrambling and by testing an external dataset of binding compounds (15 compounds for CYP2D6 and 40 for CYP2C9). To assess the probability of false-positive predictions, datasets of nonbinders (64 compounds for CYP2D6 and 56 for CYP2C9) were tested by using the same protocol. The two validated mQSAR models were subsequently added to the VirtualToxLab (VTL, http://www.virtualtoxlab.org).

Broad modifications of various positions of the minimal natural epitope recognized by the myelin-associated glycoprotein (MAG), a blocker of regeneration of neurite injuries, produced sialosides with nanomolar affinities. However, important pharmacokinetic issues, for example, the metabolic stability of these sialosides, remain to be addressed. For this reason, the novel non-carbohydrate mimic 3 was designed and synthesized from (-)-quinic acid. For the design of 3, previously identified beneficial modifications of side chains of Neu5Ac were combined with the replacement of the ring oxygen by a methylene group and the substitution of the C(4)-OH by an acetamide. Although docking experiments to a homology model of MAG revealed that mimic 3 forms all but one of the essential hydrogen bonds identified for the earlier reported lead 2, its affinity was substantially reduced. Extensive molecular-dynamics simulation disclosed that the missing hydrogen bond of the former C(8)-OH leads to a change of the orientation of the side chain. As a consequence, an important hydrophobic contact is compromised leading to a loss of affinity.

A series of novel aryl-substituted triazolyl D-galactosamine derivatives was synthesized as ligands for the carbohydrate recognition domain of the major subunit H1 (H1-CRD) of the human asialoglycoprotein receptor (ASGP-R). The compounds were biologically evaluated with a newly developed competitive binding assay, surface plasmon resonance and by a competitive NMR binding experiment. With compound 1b, a new ligand with a twofold improved affinity to the best so far known D-GalNAc was identified. This small, drug-like ligand can be used as targeting device for drug delivery to hepatocytes.

Molecular interactions of odorants with their olfactory receptors (ORs) are of central importance for the ability of the mammalian olfactory system to detect and discriminate a vast variety of odors with a limited set of receptors. How a particular OR binds and distinguishes different odorant molecules remains largely unknown on a structural basis. Here we investigated this question for the mouse eugenol receptor (mOR-EG). By screening a large odorant library, we discovered a wide range of chemical structures activating the receptor in heterologous mammalian cells. Potent agonists comprise (i) benzene, (ii) cyclohexane, or (iii) polycyclic structures substituted with alcohol, aldehyde, keto, ether, or esterified carboxylic groups. To detect those amino acids within the receptor that are in contact with a particular bound odorant molecule, we investigated how distinct mOR-EG point mutants were activated by the different odorant agonists found for the wild-type receptor. We identified 11 amino acids as a part of the receptor's ligand binding pocket. Molecular modeling predicted 10 of these residues in transmembrane helices TM3-TM6 and one in the extracellular loop between TM2 and TM3. These amino acids participate in odorant binding with variable importance depending on the type of odorant, revealing functional "fingerprints" of ligand-receptor interactions.

The tetrasaccharide 1, a substructure of ganglioside GQ1b alpha, shows a remarkable affinity for the myelin-associated glycoprotein (MAG) and was therefore selected as starting point for a lead optimization program. In our search for structurally simplified and pharmacokinetically improved mimics of 1, modifications of the core disaccharide, the alpha(2-->3)- and the alpha(2-->6)-linked sialic acid were synthesized. Biphenylmethyl and (S)-lactate were identified as suitable replacements for the alpha(2-->6)-linked sialic acid. Combined with a core modification and the earlier found aryl amide substituent in the 9-position of the alpha(2-->3)-linked sialic acid, high affinity MAG antagonists were identified. All mimics were tested in a competitive target-based binding assay, providing relative inhibitory potencies (rIP). Compared to the reference tetrasaccharide 1, the rIPs of the most potent antagonists 59 and 60 are enhanced nearly 400-fold. Their K(D)s determined in surface plasmon resonance experiments are in the low micromolar range. These results are in semiquantitative agreement with molecular modeling studies. This new class of glycomimetics will allow to validate the role of MAG in the axon regeneration process.

The glucocorticoid receptor (GR) is a member of the nuclear receptor superfamily that affects immune response, development, and metabolism in target tissues. Glucocorticoids are widely used to treat diverse pathophysiological conditions, but their clinical applicability is limited by side effects. A prediction of the binding affinity toward the GR would be beneficial for identifying glucocorticoid-mediated adverse effects triggered by drugs or chemicals. By identifying the binding mode to the GR using flexible docking (software Yeti) and quantifying the binding affinity through multidimensional QSAR (software Quasar), we validated a model family based on 110 compounds, representing four different chemical classes. The correlation with the experimental data (cross-validated r(2)=0.702; predictive r(2)=0.719) suggests that our approach is suited for predicting the binding affinity of related compounds toward the GR. After challenging the model by a series of scramble tests, a consensus approach (software Raptor), and a prediction set, it was incorporated into our VirtualToxLab and used to simulate and quantify the interaction of 24 psychotropic drugs with the GR.