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Mechanism-based Categorization of Aromatase Inhibitors: A Potential Discovery and Screening Tool
Citation:
PETKOV, P. I., S. TEMELKOV, DAN VILLENEUVE, G. T. ANKLEY, AND O. G. MEKENYAN. Mechanism-based Categorization of Aromatase Inhibitors: A Potential Discovery and Screening Tool. SAR AND QSAR IN ENVIRONMENTAL RESEARCH. Taylor & Francis, Inc., Philadelphia, PA, 20(7-8):657-678, (2009).
Impact/Purpose:
To find out if such a system could provide a screening tool to detect environmental contaminants that could act as AIs.
Description:
Cytochrome P450 aromatase is a key steroidogenic enzyme that converts androgens to estrogens in vertebrates. There is much interest in aromatase inhibitors (AIs) 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 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 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 allowing one to build a decision tree (profile) 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 could provide a screening tool to detect environmental contaminants that could act as AIs.
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Mechanism-based Categorization of Aromatase Inhibitors: A Potential Discovery and Screening Tool