Insight into the Enzyme-Inhibitor Interactions of the First Experimentally Determined Human Aromatase

In silico study for prediction of novel bioactivities of the endophytic fungal alkaloid, mycoleptodiscin B for human targets

Mycoleptodiscin B is a natural product extracted from the endophytic fungus Mycoleptodiscus sp. found in Sri Lanka and Panama with experimentally unexplored activities for human targets. In this study, a computational methodology was applied to determine druggable targets of mycoleptodiscin B. According to the computational toxicity and pharmacokinetics assessment, mycoleptodiscin B was proven to be a suitable drug candidate. Druggable targets for this compound, aromatase, acidic plasma glycoprotein and androgen receptor, were predicted using reverse docking. A two-step validation of those targets was performed using conventional molecular docking and molecular dynamic (MD) simulations, resulting in aromatase being determined as the potential therapeutic target. Based on molecular mechanics/Generalized Born Surface Area (GBSA) free energies and ligand stability inside the active site cavity during its 120 ns MD run, it can be concluded that mycoleptodiscin B is a potent aromatase inhibitor and could be subjected to further in vitro and in vivo experiments in the drug development pipeline. Consequently, natural product chemists can quickly identify the hidden medicinal properties of their miracle compounds using the computational approach applied in this research.

Human cytochrome P450 enzymes 5-51 as targets of drugs and natural and environmental compounds: mechanisms, induction, and inhibition - toxic effects and benefits

Cytochrome P450 (P450, CYP) enzymes have long been of interest due to their roles in the metabolism of drugs, pesticides, pro-carcinogens, and other xenobiotic chemicals. They have also been of interest due to their very critical roles in the biosynthesis and metabolism of steroids, vitamins, and certain eicosanoids. This review covers the 22 (of the total of 57) human P450s in Families 5-51 and their substrate selectivity. Furthermore, included is information and references regarding inducibility, inhibition, and (in some cases) stimulation by chemicals. We update and discuss important aspects of each of these 22 P450s and questions that remain open.

Comprehensive and Automated Linear Interaction Energy Based Binding-Affinity Prediction for Multifarious Cytochrome P450 Aromatase Inhibitors

Cytochrome P450 aromatase (CYP19A1) plays a key role in the development of estrogen dependent breast cancer, and aromatase inhibitors have been at the front line of treatment for the past three decades. The development of potent, selective and safer inhibitors is ongoing with in silico screening methods playing a more prominent role in the search for promising lead compounds in bioactivity-relevant chemical space. Here we present a set of comprehensive binding affinity prediction models for CYP19A1 using our automated Linear Interaction Energy (LIE) based workflow on a set of 132 putative and structurally diverse aromatase inhibitors obtained from a typical industrial screening study. We extended the workflow with machine learning methods to automatically cluster training and test compounds in order to maximize the number of explained compounds in one or more predictive LIE models. The method uses protein-ligand interaction profiles obtained from Molecular Dynamics (MD) trajectories to help model search and define the applicability domain of the resolved models. Our method was successful in accounting for 86% of the data set in 3 robust models that show high correlation between calculated and observed values for ligand-binding free energies (RMSE < 2.5 kJ mol-1), with good cross-validation statistics.

The tamoxifen metabolite norendoxifen is a potent and selective inhibitor of aromatase (CYP19) and a potential lead compound for novel therapeutic agents

To improve the treatment of breast cancer, there has been a need for alternative aromatase inhibitors (AIs) that bring about adequate aromatase inhibition, while limiting side effects. Since two tamoxifen metabolites have been documented as AIs, we tested a wide range of tamoxifen metabolites on aromatase in order to better understand structural interactions with aromatase and constructed structure-function relationships as a first step toward the development of novel inhibitors. The ability of ten tamoxifen metabolites to inhibit recombinant aromatase (CYP19) was tested using microsomal incubations. The selectivity of the most potent aromatase inhibitor identified, norendoxifen, was characterized by studying its ability to inhibit CYP450 enzymes important in clinical drug-drug interactions, including CYP2B6, 2C9, 2C19, 2D6, and 3A. Computerized molecular docking with the X-ray crystallographic structure of aromatase was used to describe the detailed biochemical interactions involved. The inhibitory potency order of the tested compounds was as follows: norendoxifen ≫ 4,4'-dihydroxy-tamoxifen > endoxifen > N-desmethyl-tamoxifen, N-desmethyl-4'-hydroxy-tamoxifen, tamoxifen-N-oxide, 4'-hydroxy-tamoxifen, N-desmethyl-droloxifene > 4-hydroxy-tamoxifen, tamoxifen. Norendoxifen inhibited recombinant aromatase via a competitive mechanism with a K ( i ) of 35 nM. Norendoxifen inhibited placental aromatase with an IC(50) of 90 nM, while it inhibited human liver CYP2C9 and CYP3A with IC(50) values of 990 and 908 nM, respectively. Inhibition of human liver CYP2C19 by norendoxifen appeared even weaker. No substantial inhibition of CYP2B6 and CYP2D6 by norendoxifen was observed. These data suggest that multiple metabolites of tamoxifen may contribute to its action in the treatment of breast cancer via aromatase inhibition. Most of all, norendoxifen may be able to serve as a potent and selective lead compound in the development of improved therapeutic agents. The range of structures tested in this study and their pharmacologic potencies provide a reasonable pharmacophore upon which to build novel AIs.