PhD Student and Teaching Assistant George Mason University fairfax, Virginia
Body of Abstract: In response to exposure to toxic agents such as herbicides and environmental pollutants, plants have developed a three-phase detoxification sequence ('green liver model') similar to mechanisms observed in mammals. The objective of this study is to use quantitative structure relationship (QSAR) analysis to understand how the chemical structure of xenobiotic chemicals affect the expression of so-called 'xenobiotic response genes', such as cytochrome P-450 monooxygenases (CYPs) and glutathione S-transferases (GSTs). Normalized gene expression data for a suite of organic chemicals, including pesticides and xenobiotic pollutants were downloaded for all confirmed and putative Arabidopsis GST/CYP genes. The QSAR analysis was performed using the software suite Alva. A comprehensive set of ~5,700 molecular descriptors was obtained for each compound and used as external variables to explain gene expression data (endogenous variables), including to the number and average expression level of CYPs and GSTs. By selecting relevant molecular descriptors models were run to determine which molecular descriptors best explain the data. Once these models were complete, they were compared to each other to find similarities and differences among the molecular descriptors used to find a best fit. The results of the QSAR analysis show models with R2 values ranging between 0.4-0.5. Among these models many of the same molecular descriptors keep showing up specifically with in two categories: functional group counts and constitutional indices. It is important to note that each model gave multiple potential models and for each model itself many of the molecular descriptors were the same when finding the best fit. This gives us confidence that the model is working instead of just assigning any or all molecular descriptors I am currently investigating the use of advanced computational applications allowing to inclusion of multiple endogenous variables (expression level of several GSTs and CYPs), such as the redundancy analysis (RDA).