In vitro interactions of abiraterone, erythromycin, and CYP3A4: implications for drug-drug interactions.

Potential drug-drug interactions of the antitumor drug abiraterone and the macrolide antibiotic erythromycin were studied at the stage of cytochrome P450 3A4 (CYP3A4) biotransformation. Using differential spectroscopy, we have shown that abiraterone is a type II ligand of CYP3A4. The dependence of CYP3A4 spectral changes on the concentration of abiraterone is sigmoidal, which indicates cooperative interactions of CYP3A4 with abiraterone; these interactions were confirmed by molecular docking. The dissociation constant (Kd ) and Hill coefficient (h) values for the CYP3A4-abiraterone complex were calculated as 3.8 ± 0.1 µM and 2.3 ± 0.2, respectively. An electrochemical enzymatic system based on CYP3A4 immobilized on a screen-printed electrode was used to show that abiraterone acts as a competitive inhibitor toward erythromycin N-demethylase activity of CYP3A4 (apparent Ki  = 8.1 ± 1.2 µM), while erythromycin and its products of enzymatic metabolism do not affect abiraterone N-oxidation by CYP3A4. In conclusion, the inhibition properties of abiraterone toward CYP3A4-dependent N-demethylation of erythromycin and the biologically inert behavior of erythromycin toward abiraterone hydroxylation were demonstrated.

Computer-aided discovery of anti-inflammatory thiazolidinones with dual cyclooxygenase/lipoxygenase inhibition.

New anti-inflammatory agents possessing dual cyclooxygenase/lipoxygenase (COX/LOX) inhibition were discovered by computer-aided prediction of biological activity for 573 virtually designed chemical compounds. Prediction of biological activity was performed by PASS, and prediction results were analyzed with PharmaExpert software. Nine 2-(thiazole-2-ylamino)-5-phenylidene-4-thiazolidinone derivatives differing by the phenyl group substitution were selected for synthesis and experimental testing as potential COX/LOX inhibitors. Eight tested compounds exhibited anti-inflammatory activity in the carrageenin-induced paw edema. It was shown that seven tested compounds (77.8%) were LOX inhibitors, seven compounds were COX inhibitors (77.8%), and six tested compounds (66.7%) were dual COX/LOX inhibitors. Analysis of lipophilicity of the compounds showed a negative correlation with inhibition of edema formation. The binding modes of the most active compounds of this series (2-(thiazole-2-ylamino)-5-( m-chlorophenylidene)-4-thiazolidinone for COX-1 and COX-2, and 2-(thiazole-2-ylamino)-5-( m-nitrophenylidene)-4-thiazolidinone for 15-LOX) were proposed on the basis of docking studies.

Rational design of macrolides by virtual screening of combinatorial libraries generated through in silico manipulation of polyketide synthases.

Bacterial secondary metabolites display diverse biological activities, thus having potential as pharmacological agents. Although most of these compounds are discovered by random screening, it is possible to predict and re-design their structures based on the information on their biosynthetic pathways. Biosynthesis of macrolides, governed by modular polyketide synthases (PKS), obeys certain rules, which can be simulated in silico. PKS mode of action theoretically allows for a huge number of macrolides to be produced upon combinatorial manipulation. Since engineering of all possible PKS variants is practically unfeasible, we created Biogenerator software, which simulates manipulation of PKS and generates virtual libraries of macrolides. These libraries can be screened by computer-aided prediction of biological activities, as exemplified by analysis of erythromycin and macrolactin libraries. This approach allows rational selection of macrolides with desired biological activities and provides instructions regarding the composition of the PKS gene clusters necessary for microbial production of such molecules.

Computer-aided selection of potential antihypertensive compounds with dual mechanism of action.

The prediction of biological activity spectra for substances as an approach for searching compounds with complex mechanisms of action was studied. New compounds with dual mechanisms of antihypertensive action were found by this approach. Biological activity spectra for substances were predicted on the basis of their structural formulas by the computer program PASS. Thirty molecular mechanisms of action of compounds from the MDDR 99.2 database, which cause the antihypertensive effect and can be predicted by PASS, have been identified. The analysis of predictions for compounds with 15 dual antihypertensive mechanisms of action from the MDDR 99.2 database has confirmed high accuracy of prediction. This approach was applied to databases of commercially available compounds (AsInEx and ChemBridge) and allowed us to select four substances that are potential inhibitors of angiotensin converting enzyme (ACE) and of neutral endopeptidase (NEP). At a later time, all these compounds were found to be the inhibitors of both ACE and NEP. The most potent compounds had IC(50) of 10(-7)-10(-9) M for ACE and 10(-5) M for NEP. New combinations of dual mechanisms of action never before found for antihypertensive compounds were predicted.

PASS biological activity spectrum predictions in the enhanced open NCI database browser.

The application of the program PASS (Prediction of Activity Spectra for Substances) to about 250 000 compounds of the NCI Open Database and the incorporation of over 64 million PASS predictions in the Enhanced NCI Database Browser are described. A total of 565 different types of activity are included, encompassing general pharmacological effects, specific mechanisms of action, known toxicities, and others. Application of this Web-based service to prediction of activities of the kinds "Angiogenesis inhibitor," "Antiviral (HIV)", and a set of activities that can be associated with antineoplastic action are reported. For this latter data set, a very substantial enrichment over random selection was found in the PASS predictions. It is shown how the user can conduct complex searches by combining ranges of PASS-predicted probabilities of compounds to be active or to be inactive, respectively, with, e.g., value ranges of physicochemical parameters, presence or absence of particular substructural fragment, and other search criteria.