Identification of novel breast cancer resistance protein (BCRP) inhibitors by virtual screening.

Breast cancer resistance protein (BCRP; ABCG2) is an efflux transporter that plays an important role in multidrug resistance to antineoplastic drugs. The identification of drugs as BCRP inhibitors could aid in designing better therapeutic strategies for cancer treatment and will be critical for identifying potential drug-drug interactions. In the present study, we applied ligand-based virtual screening combined with experimental testing for the identification of novel drugs that can possibly interact with BCRP. Bayesian and pharmacophore models generated with known BCRP inhibitors were validated with an external test set. The resulting models were applied to predict new potential drug candidates from a database with more than 2000 FDA-approved drugs. Thirty-three drugs were tested in vitro for their inhibitory effects on BCRP-mediated transport of [(3)H]-mitoxantrone in MCF-7/AdrVp cells. Nineteen drugs were identified with significant inhibitory effect on BCRP transport function. The combined strategy of computational and experimental approaches in this paper has suggested potential drug candidates and thus represents an effective tool for rational identification of modulators of other proteins.

Molecular analysis and structure-activity relationship modeling of the substrate/inhibitor interaction site of plasma membrane monoamine transporter.

Plasma membrane monoamine transporter (PMAT) is a new polyspecific transporter that interacts with a wide range of structurally diverse organic cations. To map the physicochemical descriptors of cationic compounds that allow interaction with PMAT, we systematically analyzed the interactions between PMAT and three series of structural analogs of known organic cation substrates including phenylalkylamines, n-tetraalkylammonium (n-TAA) compounds, and ß-carbolines. Our results showed that phenylalkylamines with a distance between the aromatic ring and the positively charged amine nitrogen atom of ∼6.4 Å confer optimal interactions with PMAT, whereas studies with n-TAA compounds revealed an excellent correlation between IC(50) values and hydrophobicity. The five ß-carbolines that we tested, which possess a pyridinium-like structure and are structurally related to the neurotoxin 1-methyl-4-phenylpyridinium, inhibited PMAT with high affinity (IC(50) values of 39.1-65.5 µM). Cytotoxicity analysis further showed that cells expressing PMAT are 14- to 15-fold more sensitive to harmalan and norharmanium, suggesting that these two ß-carbolines are also transportable substrates of PMAT. We then used computer-aided modeling to generate qualitative and quantitative three-dimensional pharmacophore models on the basis of 23 previously reported and currently identified PMAT inhibitors and noninhibitors. These models are characterized by a hydrogen bond donor and two to three hydrophobic features with distances between the hydrogen bond donor and hydrophobic features ranging between 5.20 and 7.02 Å. The consistency between the mapping results and observed PMAT affinity of a set of test compounds indicates that the models performed well in inhibitor prediction and could be useful for future virtual screening of new PMAT inhibitors.

Identification and validation of novel human pregnane X receptor activators among prescribed drugs via ligand-based virtual screening.

Human pregnane X receptor (hPXR) plays a key role in regulating metabolism and clearance of endogenous and exogenous substances. Identification of novel hPXR activators among commercial drugs may aid in avoiding drug-drug interactions during coadministration. We applied ligand-based computational approaches for virtual screening of a commonly prescribed drug database (SCUT). Bayesian classification models were generated with a training set comprising 177 compounds using Fingerprints and 117 structural descriptors. A cell-based luciferase reporter assay was used for evaluation of chemical-mediated hPXR activation in HepG2 cells. All compounds were tested at 10 µM concentration with rifampicin and dimethyl sulfoxide as positive and negative controls, respectively. The Bayesian models showed specificity and overall prediction accuracy up to 0.92 and 0.69 for test set compounds. Screening the SCUT database with this model retrieved 105 hits and 17 compounds from the top 25 hits were chosen for in vitro testing. The reporter assay confirmed that nine drugs, i.e., fluticasone, nimodipine, nisoldipine, beclomethasone, finasteride, flunisolide, megestrol, secobarbital, and aminoglutethimide, were previously unidentified hPXR activators. Thus, the present study demonstrates that novel hPXR activators can be efficiently identified among U.S. Food and Drug Administration-approved and commonly prescribed drugs, which should lead to detection and prevention of potential drug-drug interactions.

Membrane transporters in drug development.

Membrane transporters can be major determinants of the pharmacokinetic, safety and efficacy profiles of drugs. This presents several key questions for drug development, including which transporters are clinically important in drug absorption and disposition, and which in vitro methods are suitable for studying drug interactions with these transporters. In addition, what criteria should trigger follow-up clinical studies, and which clinical studies should be conducted if needed. In this article, we provide the recommendations of the International Transporter Consortium on these issues, and present decision trees that are intended to help guide clinical studies on the currently recognized most important drug transporter interactions. The recommendations are generally intended to support clinical development and filing of a new drug application. Overall, it is advised that the timing of transporter investigations should be driven by efficacy, safety and clinical trial enrolment questions (for example, exclusion and inclusion criteria), as well as a need for further understanding of the absorption, distribution, metabolism and excretion properties of the drug molecule, and information required for drug labelling.

Machine learning methods and docking for predicting human pregnane X receptor activation.

The pregnane X receptor (PXR) regulates the expression of genes involved in xenobiotic metabolism and transport. In vitro methods to screen for PXR agonists are used widely. In the current study, computational models for human PXR activators and PXR nonactivators were developed using recursive partitioning (RP), random forest (RF), and support vector machine (SVM) algorithms with VolSurf descriptors. Following 10-fold randomization, the models correctly predicted 82.6-98.9% of activators and 62.0-88.6% of nonactivators. The models were validated using separate test sets. The overall ( n = 15) test set prediction accuracy for PXR activators with RP, RF, and SVM PXR models is 80-93.3%, representing an improvement over models previously reported. All models were tested with a second test set ( n = 145), and the prediction accuracy ranged from 63 to 67% overall. These test set molecules were found to cover the same area in a principal component analysis plot as the training set, suggesting that the predictions were within the applicability domain. The FlexX docking method combined with logistic regression performed poorly in classifying this PXR test set as compared with RP, RF, and SVM but may be useful for qualitative interpretion of interactions within the LBD. From this analysis, VolSurf descriptors and machine learning methods had good classification accuracy and made reliable predictions within the model applicability domain. These methods could be used for high throughput virtual screening to assess for PXR activation, prior to in vitro testing to predict potential drug-drug interactions.

Camptothecins: a review of their chemotherapeutic potential.

Camptothecin analogues and derivatives appear to exert their antitumour activity by binding to topoisomerase I and have shown significant activity against a broad range of tumours. In general, camptothecins are not substrates for either the multidrug-resistance P-glycoprotein or the multidrug-resistance-associated protein (MRP). Because of manageable toxicity and encouraging activity against solid tumours, camptothecins offer promise in the clinical management of human tumours. This review illustrates the proposed mechanism(s) of action of camptothecins and presents a concise overview of current camptothecin therapy, including irinotecan and topotecan, and novel analogues undergoing clinical trails, such as exatecan (DX-8951f), IDEC-132 (9-aminocamptothecin), rubitecan (9-nitrocamptothecin), lurtotecan (GI-147211C), and the recently developed homocamptothecins diflomotecan (BN-80915) and BN-80927.