Faculty Mentor/s:  Wonpil Im, Professor of Bioengineering and Presidential Endowed Chair in Health, Science, and Engineering


Students on the team this summer:  

Kern Nathan – GRAD - Computer Science & Engineering

Stephen Gee – 2023 – UG - IBE, biocomputational engineering

Danielle Picarello -  2022 – UG - IDEAS (Bioengineering & Molecular Biology)

Grant Armstrong – 2021 – UG - Cognitive Science

Lingyang Kong – 2022 – UG - Biopharmaceutical

Tim Hartnagel – 2021 – UG - Biochemistry

Isslam Yehia – 2023 – UG - Computer Science and Engineering

Amanda Rubin -  2022 – UG - Bioengineering

Carly Cupino – 2022 – UG - Bioengineering, Biopharmaceutical track


Project Description: Despite advances in biotechnology, the number of new drugs approved per billion USD spent on drug research and development (R&D) has halved roughly every 9 years, indicating declining R&D efficiency. Therefore, the ability to conduct efficient computational drug discovery has emerged as a vital component to improve both the efficiency and economics of drug discovery. Drug compounds bind to proteins, regulating their functions to acquire beneficial effects to treat diseases. Therefore, better understanding of protein-ligand interactions at the molecular level, and accurate quantification or prediction of their binding affinity, are at the core of computer-aided drug discovery. This project aims to study protein-ligand interactions computationally, using three families of impactful therapeutic targets for cancers and AIDS: estrogen receptor; HIV-1 protease; and three types of kinases (Ser, Thr, Tyr). Out of a large number of data sets, we will choose a few test cases and compare calculated binding free energy results with the corresponding experiment data. In particular, we plan to provide practical hands-on research experiences in computer-aided drug discovery. The lectures and tools in CHARMM-GUI (http://www.charmm-gui.org/lecture) will be used for student learning and research.


Month/Year Project Began:JUNE 2020