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Berkeley ETHSTD 196 - An In Silico Prediction of ER-alpha Agonism for Quats and Phthalates

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Andrew Tantisukarom ER-alpha Agonism for Quats and Phthalates Spring 2010 1 An In Silico Prediction of ER-alpha Agonism for Quats and Phthalates Andrew Tantisukarom ABSTRACT Endocrine Disruptors are a growing concern as the female population is experiencing precocious maturation and more seriously, a greater incidence of breast cancer. Endocrine disruptors, or mimickers, can be found naturally in the environment but are most prevalent in man-made subtances. In this study, I investigated two classes of compounds- Ammonium Quaternary Compounds and Phthalates- that are less represented in the literature in respects to Estrogen Receptor-alpha (ER-a) agonism, which is linked to breast cancer. I employed Computational Toxicology, an in silico approach using state-of-the-art structure analyses modeling, specifically MDL-QSAR. The study collectively examined 70 quats and phthalates and predicted that 10 compounds showed significant ER-a agonism. KEYWORDS Computational Toxicology, Quaternary Ammonium Compound, Breast Cancer, MDL-QSAR, Endocrine DisruptorAndrew Tantisukarom ER-alpha Agonism for Quats and Phthalates Spring 2010 2 INTRODUCTION Endocrine disrupters are hormonally active agents that mimic the function of endogenous (bodily) hormones of the endocrine system, commonly referred to as the hormone system. Endocrine systems are found in all mammals, birds, fish, and many other types of living organisms. Hormones are involved in just about every biological function (Jesperson). Via the chemical system of hormones, the endocrine system regulates all biological processes in the body from conception through adulthood and into old age, including the development of the brain and nervous system, the growth and function of the reproductive system, as well as metabolism and blood sugar levels (FDA 2010). Risks of exposure to endocrine disruptors include adverse effects to the developmental, reproductive, neurological, and immune functions of humans. (National Library of Medicine 2009). Some notable examples of endocrine disrupting compounds include: Diethylstilbestrol (DES), a prescribed prenatal drug that was halted by the U.S Food and Drug Administration in 1971 because it was linked to a rare vaginal cancer (U.S. EPA 2010); Polychlorinated biphenyl (PCBs) production in the U.S. stopped in 1977 and later exports and imports in 1979 because of suspected harmful health and environmental effects; and more notoriously, Dichlorodiphenyltrichloroethane (DDT) was banned by the U.S. EPA in 1972 because it posed high risks to the environment and human health (ExtoxNet 2002). Currently, the population at greatest risk is females, as a greater number of the youth reach maturation sooner and as breast cancer rates have risen. The incidence of breast cancer was estimated to be approximately 30% greater between 1975 and 2000 (Szabo 2006). This is a result of endocrine disruption of estrogen receptors, which respond to hormones responsible for female sexual development (National Cancer Institute 2006). There are two distinct estrogen receptors in the human body: Estrogen Receptor-alpha (ER-a) and Estrogen Receptor-beta (ER-b). Both bind to the hormone Estrogen as well as other chemicals that act as agonists, receptor stimulants, or antagonists, receptor repressors. The two receptors have distinct localizations and concentrations within the body. Structural differences between the two allow for a wide range of diverse and complex bodily processes (McClure 2001).Andrew Tantisukarom ER-alpha Agonism for Quats and Phthalates Spring 2010 3 A wide range of substances, both natural and man-made, are thought to cause endocrine disruption. Endocrine disruptors may be found in many everyday products including plastic bottles, metal food cans, detergents, flame retardants, food, toys, cosmetics, and pesticides (National Library of Medicine 2009). Two classes of compounds used prevalently in industry and in day-to-day activities are Quaternary Ammonium Compounds (“Quats”) and Phthalates. Quats are commonly found in surfactants, disinfectants, and antistatic agents which are present in shampoo, spermicidal jellies, liquid fabric softeners, and dryer anticling strips. The food industry uses quats in conjunction with bleach products as a sanitizing agent. In addition, some are used in surgery as anesthetics (Rahn 1974). Phthalates are commonly found in flooring, cosmetics, soft toys, medical equipment (i.e. medical tubing, catheters and blood bags) and even air fresheners (Environmental Working Group 2007). Specifically, I am attempting to determine the estrogen-stimulating capacity, or agonism, of two chemical classes: Quats and Phthalates. I will be employing Computational Toxicology, an in silico, or computer-based, modeling method to investigate ER-a, as experiments have shown a strong link between receptor agonism and breast cancer. I am utilizing predictive chemical structure analyses models for ER-a to assess the threat of Quats and Phthalates to the female population in respect to breast cancer. METHODS The methods employed are based on Computational Toxicology principles of modeling and predicting chemical activity on a specific biological endpoint. Computational Toxicology utilizes Quantitative Structure Activity Relationship (QSAR) modeling software. MDL-QSAR was the software of choice. Figure 1 is a flow chart of how the model was built.Andre Figurare se(2007(2005activecorremeascreatethis inCompAfterone swherdiscacreatefinal TrainparamconsiAfterEC50obtainprediew Tantisukaro re 1. Modelequenced. I used th7), Kostelac 5) and the ce on ER-a, esponding Eure, as MDe a highly prnitial researcpounds (Qur, I found thespecific come SDF filesarded. A Trainied to be initMDL-QSAning Set) dmeters, I veisted of the 3r obtaining p0 values, anned an R2 vaict agonistic om l constructiohe peer-revieet al. (2003hemical datthe biologicEC50 or pEDL-QSAR prredictive moch, I also chats) and Phte SDFs, or Smpound, for s are archivng Set of 6tially exporteAR model. Aeemed “staterified its c35 remainingpredicted pEd graphing talue of greatactivity of c ER-alpha Aon flow chaewed article3), Moein et abases PubCcal endpointEC50 (-logEredicts in teodel and for hose the comthalates. TheStructure DaGroup A aved, did no9 compounded into MDLAfter arrivintistically vecapabilities g compoundEC50 values them againster


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Berkeley ETHSTD 196 - An In Silico Prediction of ER-alpha Agonism for Quats and Phthalates

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