Effect of Essential Oil Components on the Activity of Steroidogenic Cytochrome P450.

Endocrine-disrupting chemicals (EDCs) may impact the development of prostate cancer (PCa) by altering the steroid metabolism. Although their exact mechanism of action in controlling tumor growth is not known, EDCs may inhibit steroidogenic enzymes such as CYP17A1 or CYP19A1 which are involved in the production of androgens or estrogens. High levels of circulating androgens are linked to PCa in men and Polycystic Ovary Syndrome (PCOS) in women. Essential oils or their metabolites, like lavender oil and tea tree oil, have been reported to act as potential EDCs and contribute towards sex steroid imbalance in cases of prepubertal gynecomastia in boys and premature thelarche in girls due to the exposure to lavender-based fragrances. We screened a range of EO components to determine their effects on CYP17A1 and CYP19A1. Computational docking was performed to predict the binding of essential oils with CYP17A1 and CYP19A1. Functional assays were performed using the radiolabeled substrates or Liquid Chromatography-High-Resolution Mass Spectrometry and cell viability assays were carried out in LNCaP cells. Many of the tested compounds bind close to the active site of CYP17A1, and (+)-Cedrol had the best binding with CYP17A1 and CYP19A1. Eucalyptol, Dihydro-ß-Ionone, and (-)-α-pinene showed 20% to 40% inhibition of dehydroepiandrosterone production; and some compounds also effected CYP19A1. Extensive use of these essential oils in various beauty and hygiene products is common, but only limited knowledge about their potential detrimental side effects exists. Our results suggest that prolonged exposure to some of these essential oils may result in steroid imbalances. On the other hand, due to their effect on lowering androgen output and ability to bind at the active site of steroidogenic cytochrome P450s, these compounds may provide design ideas for novel compounds against hyperandrogenic disorders such as PCa and PCOS.

Exploring the Potential of Sulfur Moieties in Compounds Inhibiting Steroidogenesis.

This study reports on the synthesis and evaluation of novel compounds replacing the nitrogen-containing heterocyclic ring on the chemical backbone structure of cytochrome P450 17α-hydroxylase/12,20-lyase (CYP17A1) inhibitors with a phenyl bearing a sulfur-based substituent. Initial screening revealed compounds with marked inhibition of CYP17A1 activity. The selectivity of compounds was thereafter determined against cytochrome P450 21-hydroxylase, cytochrome P450 3A4, and cytochrome P450 oxidoreductase. Additionally, the compounds showed weak inhibitory activity against aldo-keto reductase 1C3 (AKR1C3). The compounds' impact on steroid hormone levels was also assessed, with some notable modulatory effects observed. This work paves the way for developing more potent dual inhibitors specifically targeting CYP17A1 and AKR1C3.

Non-steroidal CYP17A1 Inhibitors: Discovery and Assessment.

CYP17A1 is an enzyme that plays a major role in steroidogenesis and is critically involved in the biosynthesis of steroid hormones. Therefore, it remains an attractive target in several serious hormone-dependent cancer diseases, such as prostate cancer and breast cancer. The medicinal chemistry community has been committed to the discovery and development of CYP17A1 inhibitors for many years, particularly for the treatment of castration-resistant prostate cancer. The current Perspective reflects upon the discovery and evaluation of non-steroidal CYP17A1 inhibitors from a medicinal chemistry angle. Emphasis is placed on the structural aspects of the target, key learnings from the presented chemotypes, and design guidelines for future inhibitors.

Polypharmacology-Labeled Molecular Networking: An Analytical Technology Workflow for Accelerated Identification of Multiple Bioactive Constituents in Complex Extracts.

Discovery of sustainable and benign-by-design drugs to combat emerging health pandemics calls for new analytical technologies to explore the chemical and pharmacological properties of Nature's unique chemical space. Here, we present a new analytical technology workflow, polypharmacology-labeled molecular networking (PLMN), where merged positive and negative ionization tandem mass spectrometry-based molecular networking is linked with data from polypharmacological high-resolution inhibition profiling for easy and fast identification of individual bioactive constituents in complex extracts. The crude extract of Eremophila rugosa was subjected to PLMN analysis for the identification of antihyperglycemic and antibacterial constituents. Visually easy-interpretable polypharmacology scores and polypharmacology pie charts as well as microfractionation variation scores of each node in the molecular network provided direct information about each constituent's activity in the seven assays included in this proof-of-concept study. A total of 27 new non-canonical nerylneryl diphosphate-derived diterpenoids were identified. Serrulatane ferulate esters were shown to be associated with antihyperglycemic and antibacterial activities, including some showing synergistic activity with oxacillin in clinically relevant (epidemic) methicillin-resistant Staphylococcus aureus strains and some showing saddle-shaped binding to the active site of protein-tyrosine phosphatase 1B. PLMN is scalable in the number and types of assays included and thus holds potential for a paradigm shift toward polypharmacological natural-products-based drug discovery.

Itraconazole Reverts ABCB1-Mediated Docetaxel Resistance in Prostate Cancer.

Docetaxel (DTX) was the first chemotherapeutic agent to demonstrate significant efficacy in the treatment of men with metastatic castration-resistant prostate cancer. However, response to DTX is generally short-lived, and relapse eventually occurs due to emergence of drug-resistance. We previously established two DTX-resistant prostate cancer cell lines, LNCaPR and C4-2BR, derived from the androgen-dependent LNCaP cell line, and from the LNCaP lineage-derived androgen-independent C4-2B sub-line, respectively. Using an unbiased drug screen, we identify itraconazole (ITZ), an oral antifungal drug, as a compound that can efficiently re-sensitize drug-resistant LNCaPR and C4-2BR prostate cancer cells to DTX treatment. ITZ can re-sensitize multiple DTX-resistant cell models, not only in prostate cancer derived cells, such as PC-3 and DU145, but also in docetaxel-resistant breast cancer cells. This effect is dependent on expression of ATP-binding cassette (ABC) transporter protein ABCB1, also known as P-glycoprotein (P-gp). Molecular modeling of ITZ bound to ABCB1, indicates that ITZ binds tightly to the inward-facing form of ABCB1 thereby inhibiting the transport of DTX. Our results suggest that ITZ may provide a feasible approach to re-sensitization of DTX resistant cells, which would add to the life-prolonging effects of DTX in men with metastatic castration-resistant prostate cancer.

Synthesis and Structure-Activity Relationships of Novel Non-Steroidal CYP17A1 Inhibitors as Potential Prostate Cancer Agents.

Twenty new compounds, targeting CYP17A1, were synthesized, based on our previous work on a benzimidazole scaffold, and their biological activity evaluated. Inhibition of CYP17A1 is an important modality in the treatment of prostate cancer, which remains the most abundant cancer type in men. The biological assessment included CYP17A1 hydroxylase and lyase inhibition, CYP3A4 and P450 oxidoreductase (POR) inhibition, as well as antiproliferative activity in PC3 prostate cancer cells. The most potent compounds were selected for further analyses including in silico modeling. This combined effort resulted in a compound (comp 2, IC50 1.2 µM, in CYP17A1) with a potency comparable to abiraterone and selectivity towards the other targets tested. In addition, the data provided an understanding of the structure-activity relationship of this novel non-steroidal compound class.

Discovery of Novel Non-Steroidal Cytochrome P450 17A1 Inhibitors as Potential Prostate Cancer Agents.

The current study presents the design, synthesis, and evaluation of novel cytochrome P450 17A1 (CYP17A1) ligands. CYP17A1 is a key enzyme in the steroidogenic pathway that produces androgens among other steroids, and it is implicated in prostate cancer. The obtained compounds are potent enzyme inhibitors (sub µM) with antiproliferative activity in prostate cancer cell lines. The binding mode of these compounds is also discussed.

Promising Tools in Prostate Cancer Research: Selective Non-Steroidal Cytochrome P450 17A1 Inhibitors.

Cytochrome P450 17A1 (CYP17A1) is an important target in the treatment of prostate cancer because it produces androgens required for tumour growth. The FDA has approved only one CYP17A1 inhibitor, abiraterone, which contains a steroidal scaffold similar to the endogenous CYP17A1 substrates. Abiraterone is structurally similar to the substrates of other cytochrome P450 enzymes involved in steroidogenesis, and interference can pose a liability in terms of side effects. Using non-steroidal scaffolds is expected to enable the design of compounds that interact more selectively with CYP17A1. Therefore, we combined a structure-based virtual screening approach with density functional theory (DFT) calculations to suggest non-steroidal compounds selective for CYP17A1. In vitro assays demonstrated that two such compounds selectively inhibited CYP17A1 17α-hydroxylase and 17,20-lyase activities with IC50 values in the nanomolar range, without affinity for the major drug-metabolizing CYP2D6 and CYP3A4 enzymes and CYP21A2, with the latter result confirmed in human H295R cells.

Synthesis and antiangiogenic activity of N-alkylated levamisole derivatives.

Inhibition of angiogenesis is a promising addition to current cancer treatment strategies. Neutralization of vascular endothelial growth factor by monoclonal antibodies is clinically effective but may cause side effects due to thrombosis. Low molecular weight angiogenesis inhibitors are currently less effective than antibody treatment and are also associated with serious side effects. The discovery of new chemotypes with efficient antiangiogenic activity is therefore of pertinent interest. (S)-levamisole hydrochloride, an anthelminthic drug approved for human use and with a known clinical profile, was recently shown to be an inhibitor of angiogenesis in vitro and exhibited tumor growth inhibition in mice. Here we describe the synthesis and in vitro evaluation of a series of N-alkylated analogues of levamisole with the aim of characterizing structure-activity relationships with regard to inhibition of angiogenesis. N-methyllevamisole and p-bromolevamisole proved more effective than the parent compound, (S)-levamisole hydrochloride, with respect to inhibition of angiogenesis and induction of undifferentiated cluster morphology in human umbilical vein endothelial cells grown in co-culture with normal human dermal fibroblasts. Interestingly, the cluster morphology caused by N-methyllevamisole was different than the clusters observed for levamisole, and a third "cord-like" morphology resembling that of the known drug suramin was observed for an aniline-containing derivative. New chemotypes exhibiting antiangiogenic effects in vitro are thus described, and further investigation of their underlying mechanism of action is warranted.

In silico predictions of hERG channel blockers in drug discovery: from ligand-based and target-based approaches to systems chemical biology.

The risk for cardiotoxic side effects represents a major problem in clinical studies of drug candidates and regulatory agencies have explicitly recommended that all new drug candidates should be tested for blockage of the human Ether-a-go-go Related-Gene (hERG) potassium channel. Indeed, several drugs with different therapeutic indications and recognized as hERG blockers were recently withdrawn due to the risk of QT prolongation, arrhythmia and Torsade de Pointes. In silico techniques can provide a priori knowledge of hERG blockers, thus reducing the costs associated with screening assays. Significant progress has been made in structure-based and ligand-based drug design and a number of models have been developed to predict hERG blockage. Although approaches such as homology modeling in combination with docking and molecular dynamics bring us closer to understand the drug-channel interactions whereas QSAR and classification models provide a faster assessment and detection of hERG-related drug toxicity, limitation on the applicability domain of the current models and integration of data from diverse in vitro approaches are still issues to challenge. Therefore, this review will emphasize on current methods to predict hERG blockers and the need of consistent data to improve the quality and performance of the in silico models. Finally, integration of network-based analysis on drugs inducing potentially long-QT syndrome and arrhythmia will be discussed as a new perspective for a better understanding of the drug responses in systems chemical biology.

hERG classification model based on a combination of support vector machine method and GRIND descriptors.

The human Ether-a-go-go Related Gene (hERG) potassium channel is one of the major critical factors associated with QT interval prolongation and development of arrhythmia called Torsades de Pointes (TdP). It has become a growing concern of both regulatory agencies and pharmaceutical industries who invest substantial effort in the assessment of cardiac toxicity of drugs. The development of in silico tools to filter out potential hERG channel inhibitors in early stages of the drug discovery process is of considerable interest. Here, we describe binary classification models based on a large and diverse library of 495 compounds. The models combine pharmacophore-based GRIND descriptors with a support vector machine (SVM) classifier in order to discriminate between hERG blockers and nonblockers. Our models were applied at different thresholds from 1 to 40 microm and achieved an overall accuracy up to 94% with a Matthews coefficient correlation (MCC) of 0.86 ( F-measure of 0.90 for blockers and 0.95 for nonblockers). The model at a 40 microm threshold showed the best performance and was validated internally (MCC of 0.40 and F-measure of 0.57 for blockers and 0.81 for nonblockers, using a leave-one-out cross-validation). On an external set of 66 compounds, 72% of the set was correctly predicted ( F-measure of 0.86 and 0.34 for blockers and nonblockers, respectively). Finally, the model was also tested on a large set of hERG bioassay data recently made publicly available on PubChem ( http://pubchem.ncbi.nlm.nih.gov/assay/assay.cgi?aid=376) to achieve about 73% accuracy ( F-measure of 0.30 and 0.83 for blockers and nonblockers, respectively). Even if there is still some limitation in the assessment of hERG blockers, the performance of our model shows an improvement between 10% and 20% in the prediction of blockers compared to other methods, which can be useful in the filtering of potential hERG channel inhibitors.

Development of a QSAR model for binding of tripeptides and tripeptidomimetics to the human intestinal di-/tripeptide transporter hPEPT1.

PURPOSE: The aim of this study was to develop a three-dimensional quantitative structure-activity relationship (QSAR) model for binding of tripeptides and tripeptidomimetics to hPEPT1 based on a series of 25 diverse tripeptides. METHODS: VolSurf descriptors were generated and correlated with binding affinities by multivariate data analysis. The affinities for hPEPT1 of the tripeptides and tripeptidomimetics were determined experimentally by use of Caco-2 cell monolayers. RESULTS: The Ki-values of the 25 tripeptides and tripeptidomimetics ranged from 0.15 to 25 mM and the structural diversity of the compounds was described by VolSurf descriptors. A QSAR model that correlated the VolSurf descriptors of the tripeptides with their experimental binding affinity for hPEPT1 was established. CONCLUSION: Structural information on tripeptide properties influencing the binding to hPEPT1 was extracted from the QSAR model. This information may contribute to the drug design process of tripeptides and tripeptidomimetics where hPEPT1 is targeted as an absorptive transporter for improvement of intestinal absorption. To our knowledge, this is the first time a correlation between VolSurf descriptors and binding affinities for hPEPT1 has been reported.