Mechanism-based categorization of aromatase inhibitors: a potential discovery and screening tool

Abstract

Cytochrome P450 aromatase is a key steroidogenic enzyme that converts androgens to estrogens in vertebrates. There is much interest in aromatase inhibitors (AIs) both because of their use as pharmaceuticals in the treatment of estrogen-sensitive breast cancers, and because a number of environmental contaminants can act as AIs, thereby disrupting endocrine function in humans and wildlife through suppression of circulating estrogen levels. The goal of the current work was to develop a mechanism-based structure-activity relationship (SAR) categorization framework highlighting the most important chemical structural features responsible for inhibition of aromatase activity. Two main interaction mechanisms were discerned: steroidal and non-steroidal. The steroid scaffold is most prominent when the structure of the target chemical is similar to the natural substrates of aromatase - androstenedione and testosterone. Chemicals acting by non-steroidal mechanism(s) possess a heteroatom (N, O, S) able to coordinate the heme iron of the cytochrome P450, and thus interfere with steroid hydroxylation. The specific structural boundaries controlling AI for both analyzed mechanisms were defined, and a software tool was developed that allowed a decision tree (profile) to be built discriminating AIs by mechanism and potency. An input chemical follows a profiling path and the structure is examined at each step to decide whether it conforms with the structural boundaries implemented in the decision tree node. Such a system would aid drug discovery efforts, as well as provide a screening tool to detect environmental contaminants that could act as AIs.

Development of Novel CH223191-Based Antagonists of the Aryl Hydrocarbon Receptor

“…The differing pharmacological impact of these ligands is thought to arise from their distinct interactions with the amino acid residues that reside within the AHR ligand binding pocket and induce subtle changes in receptor conformation. Our current understanding of the molecular events involved in the interactions between the AHR ligand binding pocket and its ligands have been facilitated greatly by studies using site-directed mutagenesis and computational methodologies (Procopio et al, 2002;Henry and Gasiewicz, 2008;Bisson et al, 2009;Pandini et al, 2009;Petkov et al, 2009;Whelan et al, 2010). Within the AHR binding cavity are critical amino acid residues that ensure that the cavity is sufficiently sized to accommodate relatively large molecules such as TCDD.…”

“…In addition, amino acid residues with aromatic properties are thought to interact with and stabilize the bound ligand, whereas those with relatively high polarity participate in hydrogen bonding and other interactions. The antagonistic versus agonistic properties of these ligands appear to be dictated by the localization of charge within the ligand molecules and the distinct interactions between the ligand and the amino acid residues that lie within the AHR ligand binding pocket (Petkov et al, 2009). For example, with respect to AHR agonists, molecular docking studies (Bisson et al, 2009) have revealed that 6-formylindolo [3,2-b]carbazole can form two hydrogen bonds with glutamine residues, whereas 2-(1Ј-H-indole-3ЈЈ-carbonyl)- Table 1.…”

Breast Cancer Medications and Vision: Effects of Treatments for Early-stage Disease

“…Anastrozole and letrozole each are non-steroidal AIs that by reversibly binding to the aromatase enzyme interfere with steroidal hydroxylation, thereby inhibiting estrogen synthesis 232. Exemestane is a steroidal AI that structurally resembles the androgen androstenedione and interacts with the substrate binding site of the aromatase enzyme, ultimately leading to the enzyme's irreversible inactivation (meaning that the subsequent production of estrogen requires aromatase to be synthesized anew) 232, 233. Each AI reduces aromatization by more than 97%, with letrozole being slightly more effective in this regard than anastrozole 230.…”

Recent Progress in the Discovery of Next Generation Inhibitors of Aromatase from the Structure–Function Perspective

“…There were also efforts to develop better strategy or algorithm for in silico screening and discovering novel AIs. 16,144,150 …”