Profiling withanolide A for therapeutic targets in neurodegenerative diseases.

To identify new potential therapeutic targets for neurodegenerative diseases, we initiated activity-based protein profiling studies with withanolide A (WitA), a known neuritogenic constituent of Withania somnifera root with unknown mechanism of action. Molecular probes were designed and synthesized, and led to the discovery of the glucocorticoid receptor (GR) as potential target. Molecular modeling calculations using the VirtualToxLab predicted a weak binding affinity of WitA for GR.

In Silico Prediction of the Toxic Potential of Lupeol.

Lupeol is a natural triterpenoid found in many plant species such as mango. This compound is the principal active component of many traditional herbal medicines. In the past decade, a considerable number of publications dealt with lupeol and its analogues due to the interest in their pharmacological activities against cancer, inflammation, arthritis, diabetes, and heart disease.

VirtualToxLab: Exploring the Toxic Potential of Rejuvenating Substances Found in Traditional Medicines.

Docking and quantifying the binding of small molecules to the 3D structure of a macromolecular bioregulator by computational techniques is a typical task in R&D aimed at the design and optimization of medically or otherwise active compounds. Much less known is the fact that these methods can be successfully applied for the purpose of toxicity prediction-for example, detecting a compound's potential binding to so-called "off-targets" already at the preclinical stage. In this chapter, we provide an overview of such a computational approach, discuss its strengths and weaknesses, and include a case study-focused on natural compounds present in traditional medicines.

Molecular mechanisms of endocrine and metabolic disruption: An in silico study on antitrypanosomal natural products and some derivatives.

The VirtualToxLab is an in silico technology for estimating the toxic potential - endocrine and metabolic disruption, as well as aspects of carcinogenicity and cardiotoxicity - of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of currently 16 proteins, known or suspected to trigger adverse effects. The simulations are conducted at the atomic level and explicitly allow for a mechanistic interpretation of the results (in real-time 3D/4D), thereby complying with the Setubal principles put forward in 2002 for computational approaches to toxicology.

OpenVirtualToxLab--a platform for generating and exchanging in silico toxicity data.

The VirtualToxLab is an in silico technology for estimating the toxic potential--endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity--of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of currently 16 proteins, known or suspected to trigger adverse effects: 10 nuclear receptors (androgen, estrogen α, estrogen β, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor γ, progesterone, thyroid α, thyroid β), four members of the cytochrome P450 enzyme family (1A2, 2C9, 2D6, 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG). The toxic potential of a compound--its ability to trigger adverse effects--is derived from its computed binding affinities toward these very proteins: the computationally demanding simulations are executed in client-server model on a Linux cluster of the University of Basel.

Exploring the free-energy landscape of carbohydrate-protein complexes: development and validation of scoring functions considering the binding-site topology.

Carbohydrates play a key role in a variety of physiological and pathological processes and, hence, represent a rich source for the development of novel therapeutic agents. Being able to predict binding mode and binding affinity is an essential, yet lacking, aspect of the structure-based design of carbohydrate-based ligands. We assembled a diverse data set comprising 273 carbohydrate-protein crystal structures with known binding affinity and evaluated the prediction accuracy of a large collection of well-established scoring and free-energy functions, as well as combinations thereof.

Migration of cyclo-diBA from coatings into canned food: method of analysis, concentration determined in a survey and in silico hazard profiling.

Cyclo-diBA, the cyclic product formed from bisphenol A and bisphenol A diglycidyl ether during production of epoxy resins, was measured in canned food using reversed phase HPLC with fluorescence detection. Half (9 of 17) of the samples of canned fish in oil collected in April 2010 contained cyclo-diBA with an average concentration of 1025 μg/kg and a maximum of 1980 μg/kg. In September 2012, cyclo-diBA was detectable (>25 μg/kg) in merely 13 from 44 such products; the average concentration in these was 807 μg/kg and the maximum now reached 2640 μg/kg.

A molecular-modeling toolbox aimed at bridging the gap between medicinal chemistry and computational sciences.

In the current era of high-throughput drug discovery and development, molecular modeling has become an indispensable tool for identifying, optimizing and prioritizing small-molecule drug candidates. The required background in computational chemistry and the knowledge of how to handle the complex underlying protocols, however, might keep medicinal chemists from routinely using in silico technologies. Our objective is to encourage those researchers to exploit existing modeling technologies more frequently through easy-to-use graphical user interfaces.

VirtualToxLab - a platform for estimating the toxic potential of drugs, chemicals and natural products.

The VirtualToxLab is an in silico technology for estimating the toxic potential (endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity) of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of proteins, known or suspected to trigger adverse effects. The toxic potential, a non-linear function ranging from 0.

AcquaAlta: a directional approach to the solvation of ligand-protein complexes.

Water molecules mediating polar interactions in ligand-protein complexes can substantially contribute to binding affinity and specificity. To account for such water molecules in computer-aided drug design, we performed an extensive search in the Cambridge Structural Database (CSD) to identify the geometrical criteria defining interactions of water molecules with ligand and protein. In addition, with ab initio calculations the propensity of ligand hydration was evaluated.

From the ganglioside GQ1balpha to glycomimetic antagonists of the myelin-associated glycoprotein (MAG).

The tetrasaccharide 4, a substructure of ganglioside GQ1balpha, 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 4, antagonists with modifications of the core disaccharide Galbeta(1-3)GalNAc, as well as the terminal alpha(2-3)- and the internal alpha(2-6)-linked neuraminic acid were synthesized and tested in target-based binding assays. Compared to the reference tetrasaccharide 4, the most potent antagonist 17 exhibits a 360-fold improved affinity.

Probing small-molecule binding to cytochrome P450 2D6 and 2C9: An in silico protocol for generating toxicity alerts.

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.

Design, synthesis, biological evaluation, and modeling of a non-carbohydrate antagonist of the myelin-associated glycoprotein.

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.

Low molecular weight antagonists of the myelin-associated glycoprotein: synthesis, docking, and biological evaluation.

The injured adult mammalian central nervous system is an inhibitory environment for axon regeneration due to specific inhibitors, among them the myelin-associated glycoprotein (MAG), a member of the Siglec family (sialic-acid binding immunoglobulin-like lectin). In earlier studies, we identified the lead structure 5, which shows a 250-fold improved in vitro affinity for MAG compared to the tetrasaccharide binding epitope of GQ1balpha (1), the best physiological MAG ligand described so far. By modifying the 2- and 5-position, the affinity of 5 could be further improved to the nanomolar range (-->19a).

Probing Small-Molecule Binding to the Liver-X Receptor: A Mixed-Model QSAR Study.

The LXR model has been added in the VirtualToxLab, a fully automated technology that allows for the identification of the endocrine-disrupting potential of drugs, chemicals and natural products. This protocol has then been applied to screen a series of 161 natural compounds probing their binding to the LXR. The results of the simulation were compared with experimental data (where available) and suggest that the LXR model can be applied to predict the binding affinity of existing or hypothetical compounds for screening purposes.

In silico toxicology in drug discovery - concepts based on three-dimensional models.

Animal testing is still compulsory worldwide, for the approval of drugs and chemicals produced in large quantities. Computer-assisted (in silico) technologies are considered to be efficient alternatives to in vivo experiments, and are therefore endorsed by many regulatory agencies, e.g.

VirtualToxLab - in silico prediction of the toxic (endocrine-disrupting) potential of drugs, chemicals and natural products. Two years and 2,000 compounds of experience: a progress report.

The VirtualToxLab is an in silico tool for predicting the toxic (endocrine-disrupting) potential of drugs, chemicals and natural products. It is based on a fully automated protocol and calculates the binding affinity of any molecule of interest towards a series of 12 proteins, known or suspected to trigger adverse effects and estimates the resulting toxic potential. In contrast to other approaches in the field, the technology allows to rationalize a prediction at the molecular level by interactively analyzing the binding mode of the tested compound with any target protein in 3D.

Design, synthesis and evaluation of monovalent ligands for the asialoglycoprotein receptor (ASGP-R).

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.

Mixed-model QSAR at the human mineralocorticoid receptor: predicting binding mode and affinity of anabolic steroids.

We present a computational study on the human mineralocorticoid receptor (hMR) that is based on multi-dimensional quantitative structure-activity relationships (mQSAR). Therein, we identified the binding mode of 48 steroid and non-steroid homologues by flexible docking to the crystal structure (software Yeti) and quantified it using 6D-QSAR (software Quasar). The receptor surrogate, evolved using a genetic algorithm, converged at a cross-validated r2 of 0.

Examination of the biological role of the alpha(2-->6)-linked sialic acid in gangliosides binding to the myelin-associated glycoprotein (MAG).

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.

Mixed-model QSAR at the glucocorticoid receptor: predicting the binding mode and affinity of psychotropic drugs.

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.

VirtualToxLab - in silico prediction of the toxic potential of drugs and environmental chemicals: evaluation status and internet access protocol.

We present a receptor-modeling concept based on multidimensional QSAR (mQSAR) developed at our laboratory for the in silico prediction of the toxic potential of drugs and environmental chemicals. Presently, the VirtualToxLab includes nine so-called virtual test kits for the estrogen (alpha/beta), androgen, thyroid (alpha/beta), glucocorticoid, aryl hydrocarbon, and peroxisome proliferator-activated receptor gamma, as well as for the enzyme cytochrome P450 3A4. The surrogates have been tested against a total of 798 compounds and are able to predict the binding affinity close to the experimental uncertainty, with only six of the 188 test compounds being calculated more than a factor of 10 off the experimental binding affinity and the maximal individual deviation not exceeding a factor of 15.

Mimetics of the tri- and tetrasaccharide epitope of GQ1balpha as myelin-associated glycoprotein (MAG) ligands.

The synthesis of phenoxyphenyl, phenoxybenzyl, biphenyl, and phenyltriazole substituted sialic acid derivatives as mimics of the tri- and tetrasaccharide epitopes of GQ1balpha is described. These synthetically easily available sialosides show comparable or even enhanced affinity to MAG compared with the natural tri- and tetrasaccharide epitopes and form a new class of potential MAG antagonists.

Predicting the toxic potential of drugs and chemicals in silico: a model for the peroxisome proliferator-activated receptor gamma (PPAR gamma).

Poor pharmacokinetics, side effects and compound toxicity are frequent causes of late-stage failures in drug development. A safe in silico identification of adverse effects triggered by drugs and chemicals would therefore be highly desirable as it not only bears economical potential but also spawns a variety of ecological benefits: sustainable resource management, reduction of animal models and possibly less risky clinical trials as in silico studies are typically based on human proteins. In the recent past, our laboratory has developed a 6D-QSAR concept and validated a series of "virtual test kits" based on the aryl hydrocarbon, estrogen, androgen, thyroid, and glucocorticoid receptor as well as on the enzyme cytochrome P450 3A4.

Predicting the toxic potential of drugs and chemicals in silico.

Based on the 3D structure of the target protein (ERalphabeta, AR, PPARgamma, TRalphabeta, GR; CYP3A4) or a surrogate thereof (AhR), the Biographics Laboratory 3R has generated a series of virtual test kits and validated them against 693 compounds. In a pilot project (ToxDataBase), both existing and new drugs or environmental chemicals can be screened for their endocrine-disrupting potential or the probability to trigger drug-drug interactions in silico. After peer testing (2007-8), it is planned to make the database available on the Internet.