Abstract
OBJECTIVES/SPECIFIC AIMS: The central goal is to predict the metabolites of varenicline and predictively evaluate their propensities for eliciting an increased binding effect in the brain. METHODS/STUDY POPULATION: Molecular modeling computational software and other cheminformatic tools present a strategic in silico strategy to predict a complete metabolic transformation for the varenicline molecule. Molecular docking tools help to highlight key interactions of the varenicline with key metabolizing enzymes that are differentially expressed across a population. This will assist in validating clinical models for smoking cessation. RESULTS/ANTICIPATED RESULTS: Differentialized binding results depending on whatever metabolite is produced. DISCUSSION/SIGNIFICANCE OF IMPACT: Products of metabolism of varenicline may differ in individuals and across groups, thus, binding effects and the propensity for adverse effects may differ in individuals.