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Mechanistic Computational Model of Ovarian Steroidogenesis to Predict Biochemical Responses to Endocrine Active Compounds

Content Provider	Springer Nature Link
Author	Breen, Michael S. Villeneuve, Daniel L. Breen, Miyuki Ankley, Gerald T. Colly, Rory B.
Copyright Year	2007
Abstract	Sex steroids, which have an important role in a wide range of physiological and pathological processes, are synthesized primarily in the gonads and adrenal glands through a series of enzyme-mediated reactions. The activity of steroidogenic enzymes can be altered by a variety of endocrine active compounds (EAC), some of which are therapeutics and others that are environmental contaminants. A steady-state computational model of the intraovarian metabolic network was developed to predict the synthesis and secretion of testosterone (T) and estradiol (E2), and their responses to EAC. Model predictions were compared to data from an in vitro steroidogenesis assay with ovary explants from a small fish model, the fathead minnow. Model parameters were estimated using an iterative optimization algorithm. Model-predicted concentrations of T and E2 closely correspond to the time–course data from baseline (control) experiments, and dose–response data from experiments with the EAC, fadrozole (FAD). A sensitivity analysis of the model parameters identified specific transport and metabolic processes that most influence the concentrations of T and E2, which included uptake of cholesterol into the ovary, secretion of androstenedione (AD) from the ovary, and conversions of AD to T, and AD to estrone (E1). The sensitivity analysis also indicated the E1 pathway as the preferred pathway for E2 synthesis, as compared to the T pathway. Our study demonstrates the feasibility of using the steroidogenesis model to predict T and E2 concentrations, in vitro, while reducing model complexity with a steady-state assumption. This capability could be useful for pharmaceutical development and environmental health assessments with EAC.
Starting Page	970
Ending Page	981
Page Count	12
File Format	PDF
ISSN	00906964
Journal	Annals of Biomedical Engineering
Volume Number	35
Issue Number	6
e-ISSN	15739686
Language	English
Publisher	Kluwer Academic Publishers-Plenum Publishers
Publisher Date	2007-04-13
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Steroid biosynthesis Mathematical model Sensitivity analysis Endocrine disrupting chemicals Fadrozole Fish Cellular metabolism Biochemistry Mechanics Biophysics/Biomedical Physics Biomedical Engineering Biomedicine general
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering

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Mechanistic Computational Model of Ovarian Steroidogenesis to Predict Biochemical Responses to Endocrine Active Compounds

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