Designing Novel Compounds to PPARγ for Type II Diabetes Treatment using Free Energy Perturbation
Presentation Type
Poster Presentation
Category
STEM (science, technology, engineering, mathematics)
Abstract/Artist Statement
Peroxisome proliferator-activated receptor gamma (PPARγ) has been a target for type II diabetes treatment through the thiazolidinediones (TZDs) drug family. Unfortunately, TZDs exhibit side effects such as weight gain, congestive heart failure, and increased bone fractures, limiting their use and urging the need for safer alternatives.
This study employs Free Energy Perturbation (FEP), a computational technique used to predict binding affinities for novel compounds to a drug target. With FEP, we screened various compounds, identifying those with high binding affinity to PPARγ. Selected compounds with high binding affinities were synthesized, and their binding affinities were experimentally determined using Time-Resolved Fluorescence Resonance Energy Transfer (TR-FRET) assay.
Comparing FEP-predicted binding affinities with experimental TR-FRET data revealed a notable correlation, suggesting the efficacy of FEP in predicting ligand binding. These findings contribute to the identification and development of safer alternatives for treating type II diabetes.
Mentor Name
Travis Hughes
Designing Novel Compounds to PPARγ for Type II Diabetes Treatment using Free Energy Perturbation
UC North Ballroom
Peroxisome proliferator-activated receptor gamma (PPARγ) has been a target for type II diabetes treatment through the thiazolidinediones (TZDs) drug family. Unfortunately, TZDs exhibit side effects such as weight gain, congestive heart failure, and increased bone fractures, limiting their use and urging the need for safer alternatives.
This study employs Free Energy Perturbation (FEP), a computational technique used to predict binding affinities for novel compounds to a drug target. With FEP, we screened various compounds, identifying those with high binding affinity to PPARγ. Selected compounds with high binding affinities were synthesized, and their binding affinities were experimentally determined using Time-Resolved Fluorescence Resonance Energy Transfer (TR-FRET) assay.
Comparing FEP-predicted binding affinities with experimental TR-FRET data revealed a notable correlation, suggesting the efficacy of FEP in predicting ligand binding. These findings contribute to the identification and development of safer alternatives for treating type II diabetes.