An Approach to Teaching Structure-Activity Relationships (SAR) in the Undergraduate Chemistry Lab: Computational SAR of Polychlorinated Bisphenol Pollutant Chemicals

Undergraduate chemistry students will learn to perform simple computational chemistry calculations, how to interpret data, and use data to understand chemical behavior and phenomena. Also, students will gain reinforcement of their understanding of structure activity relationships as they relate to environmental pollutants

The lab activity is designed for senior level chemistry majors in physical chemistry. Before performing the lab, students will have had at least one course in statistics and an introduction to computational chemistry software and methods. Ideally, students will have had some experience in programming. The activity is situated in the course to reinforce prior class lectures on quantum mechanics in prediction. This lab can be completed in three lab periods.

The following are needed for this activity: computers (at least 2GB RAM), a web browser, molecular modeling software, Anaconda (Python distribution), and a text editor. In the first week, students model the systems using the modeling software and convert the models to an appropriate chemical format. In week two, students use python to calculate molecular properties. Week three of the activity consists of students using statistical methods to eliminate low- and non-correlated properties.

Although it is ideal for a student to have programming experience using python, python has recently developed a user friendly graphical user interface that nearly eliminates the need for students to know python code. This can be used instead of traditional coding.

This activity has not been implemented yet, but it is hoped that the student will write a formal lab report.