JUPITER, Fla. — Using a blend of computer modeling, structural and cell-based studies, scientists at The Wertheim UF Scripps Institute have designed a group of potential diabetes drugs that reprogram insulin-resistant cells into a healthier state while limiting side effect risks of older medications.
An estimated 36 million people in the United States live with Type 2 diabetes, a condition that develops when the body becomes resistant to insulin, the hormone that enables cells to metabolize sugar. About a third of people with this condition also have chronic kidney disease, complicating their treatment options.
In a new study, molecular biologist Patrick Griffin , Ph.D., scientific director of The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology , and his graduate student, Kuang-Ting Kuo, describe their methods for developing potential insulin-sensitizing medications. The compounds target a master regulator of fat cell and insulin metabolism called PPAR gamma. The protein plays a role in diabetes, inflammation, cancers, obesity, heart disease and osteoporosis, making it a sought-after, but complex, medicinal target.
Short for Peroxisome Proliferator-Activated Receptor gamma, the PPAR gamma protein is a type of nuclear receptor, meaning it binds to the cell's DNA, and can switch clusters of genes on and off.
The team's research was published online last month in the journal Nature Communications.
Type 2 diabetes patients need better options, Griffin said. Uncontrolled, the condition can lead to heart disease, nerve and blood vessel damage, cognitive decline, vision problems and more. The front-line drug for Type 2 diabetes, metformin, doesn't adequately improve insulin sensitivity, especially for high-risk patients with chronic kidney disease, he said. Newer diabetes drugs also carry risks for kidney disease patients, he said.
"PPAR gamma has been a notoriously difficult target, but it remains an essential one for helping patients who still lack safe, effective options," Griffin said. "What this study shows is that with the right tools and careful design, we can finally begin to overcome those barriers."
To achieve their goals, Griffin's researchers used technologies including biochemical testing, an analytical technique called hydrogen-deuterium exchange mass spectrometry (HDX), and computer-based modeling performed on HiPerGator, the University of Florida's supercomputer.
Biochemical tests measured how the compounds affected PPAR gamma activity in biological systems. HDX, a method that tracks subtle changes in protein shape, allowed the team to see how the different compounds influenced the structure and behavior of the PPAR gamma protein. And HiPerGator enabled the researchers to simulate the motion and flexibility of the protein connected with the best of the compounds. After the simulations, the team evaluated the compounds' ability to improve insulin sensitivity using both mouse and human fat cells.
"Our approach provides a transferable framework that can be applied to other drug discovery efforts targeting complex signaling proteins," Kuo said. "By combining computer modeling with structural measurements and cell-based testing, we can more efficiently identify compounds with favorable biological effects."
The researchers next plan to study how the compounds behave in more complex biological systems, including how they affect different body tissues, Kuo said.
Developing medications that target PPAR gamma has been challenging, because of the multifaceted role it plays in biology. Several diabetes drugs known as glitazones, including Actos and Avandia, robustly improve insulin sensitivity by targeting PPAR gamma. However, they are also associated with serious side effects affecting the heart, bones, and, in some cases, cancer risk.
The U.S. Food and Drug Administration mandates a boxed warning for all glitazones, highlighting their potential to cause or exacerbate congestive heart failure.
The Griffin laboratory has spent more than 15 years developing alternative compounds that fine-tune PPAR gamma activity. The new approach should allow researchers to more accurately predict therapeutic outcomes based on compound design before drugs move into later stages of testing, the scientists said.
Even with the power of HiPerGator, one of the fastest supercomputers in academia, the project stretched computing resources, Kuo said.
"A single 100-nanosecond molecular dynamics simulation took about six hours on HiPerGator," Kuo said. "With 26 compounds and three independent simulations per compound, the total computing time approached 20 days."
Future studies will explore how downstream molecules interact with the PPAR gamma-targeting compounds, Griffin said.
"Seeing this research accelerate in ways that directly address urgent patient needs is deeply gratifying," he said. "We're committed to translating these findings into clinical progress."
