Analogues of the pan-selectin antagonist rivipansel (GMI-1070).

The selectin family consisting of E-, P- and L-selectin plays dominant roles in atherosclerosis, ischemia-reperfusion injury, inflammatory diseases, and metastatic spreading of some cancers. An early goal in selectin-targeted drug discovery campaigns was to identify ligands binding to all three selectins, so-called pan-selectin antagonists. The physiological epitope, tetrasaccharide sialyl Lewisx (sLex, 1) binds to all selectins, albeit with very different affinities. Whereas P- and L-selectin require additional interactions contributed by sulfate groups for high binding affinity, E-selectin can functionally bind sLex-modified glycolipids and glycoproteins. Rivipansel (3) marked the first pan-selectin antagonist, which simultaneously interacted with both the sLex and the sulfate binding site. The aim of this contribution was to improve the pan-selectin affinity of rivipansel (3) by leveraging a new class of sLex mimetics in combination with an optimized linker length to the sulfate bearing group. As a result, the pan-selectin antagonist 11b exhibits an approximatively 5-fold improved affinity for E-, as well as P-selectin.

In silico and in vitro assessment of drugs potentially causing adverse effects by inhibiting CYP17A1.

Cytochrome P450 enzymes (CYPs) play a crucial role in the metabolism and synthesis of various compound classes. While drug-metabolizing CYP enzymes are frequently investigated as anti-targets, the inhibition of CYP enzymes involved in adrenal steroidogenesis is not well studied. The steroidogenic enzyme CYP17A1 is a dual-function enzyme catalyzing hydroxylase and lyase reactions relevant for the biosynthesis of adrenal glucocorticoids and androgens. Inhibition of CYP17A1-hydroxylase leads to pseudohyperaldosteronism with subsequent excessive mineralocorticoid receptor activation, hypertension and hypokalemia. In contrast, specific inhibition of the lyase function might be beneficial for the treatment of prostate cancer by decreasing adrenal androgen levels. This study combined in silico and in vitro methods to identify drugs inhibiting CYP17A1. The most potent CYP17A1 inhibitors identified are serdemetan, mocetinostat, nolatrexed, liarozole, and talarozole. While some of these drugs are currently under investigation for the treatment of various cancers, their potential for the treatment of prostate cancer is yet to be explored. The DrugBank database was screened for CYP17A1 inhibitors, to increase the awareness for the risk of drug-induced pseudohyperaldosteronism and to highlight drugs so far unknown for their potential to cause side effects resulting from CYP17A1 inhibition.

A battery of in silico models application for pesticides exerting reproductive health effects: Assessment of performance and prioritization of mechanistic studies.

Given the high attention to endocrine disrupting chemicals (EDC), there is an urgent need for the development of rapid and reliable approaches for the screening of large numbers of chemicals with respect to their endocrine disruption potential. This study aimed at the assessment of the correlation between the predicted results of a battery of in silico tools and the reported observed adverse effects from in vivo reproductive toxicity studies. We used VirtualToxLab (VTL) software and the EndocrineDisruptome (ED) online tool to evaluate the binding affinities to nuclear receptors of 17 pesticides, 7 of which were classified as reprotoxic substances under Regulation (EC) No 1272/2008 on the classification, labelling and packaging of substances and mixtures (CLP). Then, we aligned the results of the in silico modelling with data from ToxCast assays and in vivo reproductive toxicity studies. We combined results from different in silico tools in two different ways to improve the characteristics of their predictive performance. Reproductive toxicity can be caused by various mechanisms; however, in this study, we demonstrated that the use of a battery of in silico tools for assessing the binding to nuclear receptors can be useful for identifying hazardous compounds and for prioritizing further studies.

St. John's Wort Formulations Induce Rat CYP3A23-3A1 Independent of Their Hyperforin Content.

The pregnane X receptor (PXR) is a ligand-activated regulator of cytochrome P450 (CYP)3A enzymes. Among the ligands of human PXR is hyperforin, a constituent of St John's wort (SJW) extracts and potent inducer of human CYP3A4. It was the aim of this study to compare the effect of hyperforin and SJW formulations controlled for its content on CYP3A23-3A1 in rats. Hyperiplant was used as it contains a high hyperforin content and Rebalance because it is controlled for a low hyperforin content. In silico analysis revealed a weak hyperforin-rPXR binding affinity, which was further supported in cell-based reporter gene assays showing no hyperforin-mediated reporter activation in presence of rPXR. However, cellular exposure to Hyperiplant and Rebalance transactivated the CYP3A reporter 3.8-fold and 2.8-fold, respectively, and they induced Cyp3a23-3a1 mRNA expression in rat hepatoma cells compared with control 48-fold and 18-fold, respectively. In Wistar rats treated for 10 days with 400 mg/kg of Hyperiplant, we observed 1.8 times the Cyp3a23-3a1 mRNA expression, a 2.6-fold higher CYP3A23-3A1 protein amount, and a 1.6-fold increase in activity compared with controls. For Rebalance we only observed a 1.8-fold hepatic increase of CYP3A23-3A1 protein compared with control animals. Even though there are differing effects on rCyp3a23-3a1/CYP3A23-3A1 in rat liver reflecting the hyperforin content of the SJW extracts, the modulation is most likely not linked to an interaction of hyperforin with rPXR. SIGNIFICANCE STATEMENT: Treatment with St John's wort (SJW) has been reported to affect CYP3A expression and activity in rats. Our comparative study further supports this finding but shows that the pregnane X receptor-ligand hyperforin is not the driving force for changes in rat CYP3A23-3A1 expression and function in vivo and in vitro. Importantly, CYP3A induction mimics findings in humans, but our results suggest that another so far unknown constituent of SJW is responsible for the expression- and function-modifying effects in rat liver.

Ligand pathways in estrogen-related receptors.

The three subtypes of estrogen-related receptors ERRα, ERRß, and ERRγ are nuclear receptors mediating metabolic processes in various tissues such as the skeletal muscle, fat tissue, bone, and liver. Although the knowledge on their physiological ligands is limited, they have been implicated as drug targets for important indications including diabetes, cardiovascular diseases, and osteoporosis. As in other nuclear receptors, their ligand binding pocket is buried within the core of the receptor and connected to its surrounding by ligand pathways. Here, we investigated these pathways with conventional molecular dynamics as well as metadynamics simulations to reveal their distribution and their capability to facilitate ligand translocation. Dependent on the ERR subtype and the conformational state of the receptor, we could detect different pathways to be favored. Overall, the results suggested pathways IIIa and IIIb to be favored in the agonistic conformation, while antagonists preferred pathways I, II, and V. Along the pathways, the ligands passed different gating mechanisms of the receptor, including groups of protein residues as well as whole secondary structure elements, to leave the binding site. Even though these pathways are suggested to influence ligand specificity of the receptors and their elucidation might advance rational drug design, they have not yet been studied in ERRs.Communicated by Ramaswamy H. Sarma.

A Dimerosesquiterpene and Sesquiterpene Lactones from Artemisia argyi Inhibiting Oncogenic PI3K/AKT Signaling in Melanoma Cells.

A library of more than 2500 plant extracts was screened for activity on oncogenic signaling in melanoma cells. The ethyl acetate extract from the aerial parts of Artemisia argyi displayed pronounced inhibition of the PI3K/AKT pathway. Active compounds were tracked with the aid of HPLC-based activity profiling, and altogether 21 active compounds were isolated, including one novel dimerosequiterpenoid (1), one new disesquiterpenoid (2), three new guaianolides (3-5), 12 known sesquiterpenoids (6-17), and four known flavonoids (19-22). A new eudesmanolide derivative (13b) was isolated as an artifact formed by methanolysis. Compound 1 is the first adduct comprising a sesquiterpene lactone and a methyl jasmonate moiety. The absolute configurations of compounds 1 and 3-18 were established by comparison of their experimental and calculated ECD spectra. The absolute configuration for 2 was determined by X-ray diffraction analysis. Guaianolide 8 was the most potent sesquiterpene lactone, inhibiting the PI3K/AKT pathway with an IC50 value of 8.9 ± 0.9 µM.

Activation of retinoic acid-related orphan receptor γ(t) by parabens and benzophenone UV-filters.

Retinoic acid-related orphan receptor γt (RORγt) regulates immune responses and its impaired function contributes to inflammatory and autoimmune diseases and may promote skin cancer. Synthetic inverse RORγt agonists block the production of Th17-associated cytokines including interleukin (IL)-17A and IL-22 and are under investigation for treatment of such pathologies. Unintentional RORγt activation in skin, following exposure to environmental chemicals, may promote inflammatory skin disease. Parabens and UV-filters, frequently used as additives in cosmetics and body care products, are intensively inspected for endocrine disrupting properties. This study assessed whether such compounds can interfere with RORγ activity using a previously established tetracycline-inducible reporter gene assay in CHO cells. These transactivation experiments revealed hexylparaben, benzylparaben and benzophenone-10 as RORγ agonists (EC50 values: 144 ± 97 nM, 3.39 ± 1.74 µM and 1.67 ± 1.04 µM, respectively), and they could restore RORγ activity after suppression by an inverse agonist. Furthermore, they enhanced RORγt-dependent transcription of the pro-inflammatory IL-17A and/or IL-22 genes in the murine T-cell model EL4. Virtual screening of a cosmetics database for structurally similar chemicals and in vitro testing of the most promising hits revealed benzylbenzoate, benzylsalicylate and 4-methylphenylbenzoate as RORγ agonists (low micromolar EC50 values). Moreover, an analysis of mixtures of the newly identified RORγ agonists suggested additive effects. This study presents novel RORγ(t) agonistic structural scaffolds. By activating RORγ(t) the identified parabens and UV-filters may potentially aggravate pathophysiological conditions, especially skin diseases where highest exposure of such chemicals can be expected. Follow-up studies should assess whether such compounds, either alone or as mixtures, can reach relevant concentrations in tissues and target cells to activate RORγ(t) in vivo.

A Conserved Allosteric Site on Drug-Metabolizing CYPs: A Systematic Computational Assessment.

Cytochrome P450 enzymes (CYPs) are the largest group of enzymes involved in human drug metabolism. Ligand tunnels connect their active site buried at the core of the membrane-anchored protein to the surrounding solvent environment. Recently, evidence of a superficial allosteric site, here denoted as hotspot 1 (H1), involved in the regulation of ligand access in a soluble prokaryotic CYP emerged. Here, we applied multi-scale computational modeling techniques to study the conservation and functionality of this allosteric site in the nine most relevant mammalian CYPs responsible for approximately 70% of drug metabolism. In total, we systematically analyzed over 44 µs of trajectories from conventional MD, cosolvent MD, and metadynamics simulations. Our bioinformatic analysis and simulations with organic probe molecules revealed the site to be well conserved in the CYP2 family with the exception of CYP2E1. In the presence of a ligand bound to the H1 site, we could observe an enlargement of a ligand tunnel in several members of the CYP2 family. Further, we could detect the facilitation of ligand translocation by H1 interactions with statistical significance in CYP2C8 and CYP2D6, even though all other enzymes except for CYP2C19, CYP2E1, and CYP3A4 presented a similar trend. As the detailed comprehension of ligand access and egress phenomena remains one of the most relevant challenges in the field, this work contributes to its elucidation and ultimately helps in estimating the selectivity of metabolic transformations using computational techniques.

Computational Assessment of Combination Therapy of Androgen Receptor-Targeting Compounds.

The ligand-binding domain of the androgen receptor (AR) is a target for drugs against prostate cancer and offers three distinct binding sites for small molecules. Drugs acting on the orthosteric hormone binding site suffer from resistance mechanisms that can, in the worst case, reverse their therapeutic effect. While many allosteric ligands targeting either the activation function-2 (AF-2) or the binding function-3 (BF-3) have been reported, their potential for simultaneous administration with currently prescribed antiandrogens was disregarded. Here, we report results of 60 µs molecular dynamics simulations to investigate combinations of orthosteric and allosteric AR antagonists. Our results suggest BF-3 inhibitors to be more suitable in combination with classical antiandrogens as opposed to AF-2 inhibitors based on binding free energies and binding modes. As a mechanistic explanation for these observations, we deduced a structural adaptation of helix-12 involved in the formation of the AF-2 site by classical AR antagonists. Additionally, the changes were accompanied by an expansion of the orthosteric binding site. Considering our predictions, the selective combination of AR-targeting compounds may improve the treatment of prostate cancer.

Potential Inhibitors for Novel Coronavirus Protease Identified by Virtual Screening of 606 Million Compounds.

The rapid outbreak of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China followed by its spread around the world poses a serious global concern for public health. To this date, no specific drugs or vaccines are available to treat SARS-CoV-2 despite its close relation to the SARS-CoV virus that caused a similar epidemic in 2003. Thus, there remains an urgent need for the identification and development of specific antiviral therapeutics against SARS-CoV-2. To conquer viral infections, the inhibition of proteases essential for proteolytic processing of viral polyproteins is a conventional therapeutic strategy. In order to find novel inhibitors, we computationally screened a compound library of over 606 million compounds for binding at the recently solved crystal structure of the main protease (Mpro) of SARS-CoV-2. A screening of such a vast chemical space for SARS-CoV-2 Mpro inhibitors has not been reported before. After shape screening, two docking protocols were applied followed by the determination of molecular descriptors relevant for pharmacokinetics to narrow down the number of initial hits. Next, molecular dynamics simulations were conducted to validate the stability of docked binding modes and comprehensively quantify ligand binding energies. After evaluation of potential off-target binding, we report a list of 12 purchasable compounds, with binding affinity to the target protease that is predicted to be more favorable than that of the cocrystallized peptidomimetic compound. In order to quickly advise ongoing therapeutic intervention for patients, we evaluated approved antiviral drugs and other protease inhibitors to provide a list of nine compounds for drug repurposing. Furthermore, we identified the natural compounds (-)-taxifolin and rhamnetin as potential inhibitors of Mpro. Rhamnetin is already commercially available in pharmacies.

Allosteric Binding Sites On Nuclear Receptors: Focus On Drug Efficacy and Selectivity.

Nuclear receptors (NRs) are highly relevant drug targets in major indications such as oncologic, metabolic, reproductive, and immunologic diseases. However, currently, marketed drugs designed towards the orthosteric binding site of NRs often suffer from resistance mechanisms and poor selectivity. The identification of two superficial allosteric sites, activation function-2 (AF-2) and binding function-3 (BF-3), as novel drug targets sparked the development of inhibitors, while selectivity concerns due to a high conservation degree remained. To determine important pharmacophores and hydration sites among AF-2 and BF-3 of eight hormonal NRs, we systematically analyzed over 10 µ s of molecular dynamics simulations including simulations in explicit water and solvent mixtures. In addition, a library of over 300 allosteric inhibitors was evaluated by molecular docking. Based on our results, we suggest the BF-3 site to offer a higher potential for drug selectivity as opposed to the AF-2 site that is more conserved among the selected receptors. Detected similarities among the AF-2 sites of various NRs urge for a broader selectivity assessment in future studies. In combination with the Supplementary Material, this work provides a foundation to improve both selectivity and potency of allosteric inhibitors in a rational manner and increase the therapeutic applicability of this promising compound class.

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. Neurite outgrowth experiments in human neuroblastoma SH-SY5Y cells further supported a glucocorticoid-dependent mechanism, finding that WitA was able to reverse the outgrowth inhibition mediated by dexamethasone (Dex). However, further GR binding and transactivation assays found no direct interference of WitA. Further molecular modeling analysis suggested that WitA, although forming several contacts with residues in the GR binding pocket, is lacking key stabilizing interactions as observed for Dex. Taken together, the data suggest that WitA-dependent induction of neurite outgrowth is not through a direct effect on GR, but might be mediated through a closely related pathway. Further experiments should evaluate a possible role of GR modulators and/or related signaling pathways such as ERK, Akt, NF-κB, TRα, or Hsp90 as potential targets in the WitA-mediated neuromodulatory effects.

Using bisphenol A and its analogs to address the feasibility and usefulness of the CALUX-PPARγ assay to identify chemicals with obesogenic potential.

Environmental chemical exposures have been implicated in the obesity epidemic as potential mis-regulators of a variety of metabolic pathways. As agonism of the peroxisome proliferator-activated nuclear hormone receptor γ (PPARγ) is one of the suspected mechanisms involved, a PPARγ screening assay may have relevance for the biodetection of such effects of environmental chemicals. To test this hypothesis, we established the PPARγ2-CALUX® assay in-house and tested it against a number of known and suspected PPARγ modulators. Furthermore, we added a rat liver S9 metabolizing system to the protocol to introduce metabolic competence to the assay. Our results confirmed the responsiveness of the cell line to the known PPARγ agonists and antagonists: rosiglitazone, tributyltin, 15-deoxy-Δ12,14-prostaglandin J2, GW9662 and diclofenac. These data are in agreement with previous studies in various models. Seven bisphenol analogs tested induced little to no agonist activity, but all demonstrated antagonistic properties. These findings were contrary to both our assumptions and literature reports. Addition of the S9-metabolizing system to each of these tests did not alter any of the measured activities. Taken together, it seems probable that there are additional obesogenic effects of these chemicals which would not be detected by this assay.

Endocrine Disruption at the Androgen Receptor: Employing Molecular Dynamics and Docking for Improved Virtual Screening and Toxicity Prediction.

The androgen receptor (AR) is a key target for the development of drugs targeting hormone-dependent prostate cancer, but has also an important role in endocrine disruption. Reliable prediction of the binding of ligands towards the AR is therefore of great relevance. Molecular docking is a powerful computational method for exploring small-ligand binding to proteins. It can be applied for virtual screening experiments but also for predicting molecular initiating events in toxicology. However, in case of AR, there is no antagonist-bound crystal structure yet available. Our study demonstrates that molecular docking approaches are not able to satisfactorily screen for AR antagonists because of this reason. Therefore, we applied Molecular Dynamics simulations to generate antagonist AR structures and showed that this leads to a vast improvement for the docking of AR antagonists. We benchmarked the ability of these antagonist AR structures discriminate between AR antagonists and decoys using an ensemble docking approach and obtained promising results with good enrichment. However, distinguishing AR antagonists from agonists with high confidence is not possible with the current approach alone.

Caco-2 Permeability Studies and In Vitro hERG Liability Assessment of Tryptanthrin and Indolinone.

Tryptanthrin and (E,Z)-3-(4-hydroxy-3,5-dimethoxybenzylidene)indolinone (indolinone) were recently isolated from Isatis tinctoria as potent anti-inflammatory and antiallergic alkaloids, and shown to inhibit COX-2, 5-LOX catalyzed leukotriene synthesis, and mast cell degranulation at low µM to nM concentrations. To assess their suitability for oral administration, we screened the compounds in an in vitro intestinal permeability assay using human colonic adenocarcinoma cells. For exact quantification of the compounds, validated UPLC-MS/MS methods were used. Tryptanthrin displayed high permeability (apparent permeability coefficient > 32.0 × 10(-6) cm/s) across the cell monolayer. The efflux ratio below 2 (< 1.12) and unchanged apparent permeability coefficient values in the presence of the P-glycoprotein inhibitor verapamil (50 µM) indicated that tryptanthrin was not involved in P-glycoprotein interactions. For indolinone, a low recovery was found in the human colon adenocarcinoma cell assay. High-resolution mass spectrometry pointed to extensive phase II metabolism of indolinone (sulfation and glucuronidation). Possible cardiotoxic liability of the compounds was assessed in vitro by measurement of an inhibitory effect on human ether-a-go-go-related gene tail currents in stably transfected HEK 293 cells using the patch clamp technique. Low human ether-a-go-go-related gene inhibition was found for tryptanthrin (IC50 > 10 µM) and indolinone (IC50 of 24.96 µM). The analysis of compounds using various in silico methods confirmed favorable pharmacokinetic properties, as well as a slight inhibition of the human ether-a-go-go-related gene potassium channel at micromolar concentrations.

Labdane Diterpenoids from Salvia leriifolia: Absolute Configuration, Antimicrobial and Cytotoxic Activities.

Fractionation of an n-hexane extract of the aerial parts of Salvia leriifolia led to the isolation of two new (1, 2) and two known (3, 4) labdane diterpenoids, together with three other known compounds. The structures were established by a combination of 1D and 2D NMR, and HRESIMS. The structures of 1 and 3 were confirmed by single-crystal X-ray analysis. The absolute configuration of 1-4 was established by electronic circular dichroism spectroscopy. Compounds 1-4 were evaluated for their cytotoxic activities against MCF-7 human breast cancer cells. Labdanes 3 and 4 were additionally tested against MDA-MB231 human breast cancer and DU-145 human prostate cancer cell lines. Compound 4 showed IC50 values of 25, 50, and 50 µM against MCF-7, MDA-MB231, and DU-145 cells, respectively. Compounds 1-4 were tested for activity against gram-positive (Staphylococcus aureus) and gram-negative (Escherichia coli) bacteria. Compound 3 showed an MIC of 213 µM against methicillin-resistant S. aureus.

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 ß, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor γ, progesterone, thyroid α, thyroid ß), 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. The graphical-user interface supports all computer platforms, allows building and uploading molecular structures, inspecting and downloading the results and, most important, rationalizing any prediction at the atomic level by interactively analyzing the binding mode of a compound with its target protein(s) in real-time 3D. Access to the VirtualToxLab is available free of charge for universities, governmental agencies, regulatory bodies and non-profit organizations.

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 0.0 (none) to 1.0 (extreme), is derived from the individual binding affinities of a compound towards currently 16 target proteins: 10 nuclear receptors (androgen, estrogen α, estrogen ß, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor γ, progesterone, thyroid α, and thyroid ß), four members of the cytochrome P450 enzyme family (1A2, 2C9, 2D6, and 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG). The interface to the technology allows building and uploading molecular structures, viewing and downloading results and, most importantly, rationalizing any prediction at the atomic level by interactively analyzing the binding mode of a compound with its target protein(s) in real-time 3D. The VirtualToxLab has been used to predict the toxic potential for over 2500 compounds: the results are posted on http://www.virtualtoxlab.org. The free platform - the OpenVirtualToxLab - is accessible (in client-server mode) over the Internet. It is free of charge for universities, governmental agencies, regulatory bodies and non-profit organizations.

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. The technology is accessible over the Internet (via a secure SSH protocol) and available for any science-oriented organization. The toxic potential - a complex value derived from the individual binding affinities, their standard deviation and the quality of the underlying model (number and ratio of training and test compounds, activity range covered) - of existing and hypothetical compounds is estimated by simulating and quantifying their interactions towards a series of macromolecular targets at the molecular level using automated flexible docking combined with multidimensional QSAR (mQSAR). Currently, those targets comprise 12 proteins: the androgen, aryl hydrocarbon, estrogen alpha/beta, glucocorticoid, mineralocorticoid, thyroid alpha/beta liver X and the peroxisome proliferator-activated receptor gamma as well as the enzymes cytochrome P450 3A4 (CYP 3A4) and 2A13 (CYP 2A13). Up to date, the technology has been used to predict the toxic potential for more than 2,000 drugs, chemicals and natural compounds. All results are posted in the Internet - in this account, a few will be discussed in detail with reference to the molecular mechanisms triggering the adverse effect.

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. These results suggest that our approach is suited for the in silico identification of adverse effects triggered by drugs and environmental chemicals. In this account, we summarise the current evaluation status of the models and introduce an Internet access portal, immediately available to selected laboratories, and aimed at a peer evaluation of our concept.