Clemson researchers will use high-tech computer modeling to learn more about how proteins can play a role in the development of Type 2 diabetes.

Clemson researchers will use high-tech computer modeling to learn more about how proteins can play a role in the development of Type 2 diabetes.
Image Credit: Feng Ding lab

CLEMSON, South Carolina — A pair of Clemson University scientists is using high-tech computer modeling and experimental validation techniques to unveil the intricate molecular causes of adult-onset diabetes, one of the world’s most widespread, damaging and costly diseases.

Increased incidences of obesity, poor diet and lack of physical activity have contributed to a disturbing rise in the number of people afflicted with adult-onset diabetes. Clinically known as Type 2 diabetes, the disease affects tens of millions in the United States and hundreds of millions across the globe.

In an ongoing effort to find higher-quality therapeutic treatments, Clemson researchers Feng Ding and Weiguo Cao recently received a collaborative $1.8 million grant from the National Institutes of Health to attain a deeper understanding of how a peptide protein co-secreted with insulin in the pancreas is associated with beta cell death and subsequent insulin deficiencies. The primary function of beta cells is to produce and store insulin, a hormone that regulates the amount of glucose in the blood.

“We use computer modeling to understand the molecular mechanisms in the pancreas where insulin is produced and then we make predictions based off the models,” said Ding, an assistant professor of biophysics in the College of Science who is the principal investigator of the grant. “After that, we employ biophysical and biochemical methods to validate our predictions. Finally, we will be able to design therapeutic approaches based on what we’ve learned. This combined computational and experimental approach can improve research efficiency and significantly shorten the discovery cycle.”

In people who are not diabetic, the peptide hormone called islet amyloid polypeptide (IAPP) helps to regulate blood-sugar levels and also slows emptying of the stomach, the latter of which plays a crucial role in how much and how often we feel the need to eat. Proteins such as IAPP (also known as amylin) are composed of a coiled chain of amino acids. For those who have prediabetes or Type 2 diabetes, it is hypothesized that the entanglement of uncoiled amylin, promoted by overproduction of insulin and amylin due to insulin resistance in the pre-diabetic stage, creates a toxic environment that kills beta cells and leads to full-blown diabetes.

“In our bodies, proteins are the workhorses. And in order for these proteins to function, they need to fold into a particular shape,” said Cao, a professor of biochemistry in the College of Science who is a collaborative investigator for the grant. “If they unfold, they stretch into long chains that tend to stick together. And once many of them stick together, they become what is called an aggregate, which interferes with the biological processes within the pancreas and causes beta cells to function abnormally and eventually die.”

Ding’s simulations generate large amounts of data, most of which is produced and analyzed via the Palmetto Cluster, Clemson University’s highly regarded supercomputer. With the computational models as the initial impetus, Ding and Cao will investigate anti-aggregation approaches from three novel directions:

  • First, they will study how the internal mechanisms of healthy individuals are able to maintain their effectiveness and prevent IAPP aggregation.
  • Then they will examine how naturally occurring plant-based molecules that are known to regulate biological processes can play a role in inhibiting IAPP aggregation.
  • Finally, they will design new microscopic materials that can aid in the inhibition of IAPP aggregation and also transport medicines between and within cells with vastly improved efficiency.
Weiguo Cao is a professor of biochemistry in the College of Science and a collaborative investigator for the grant.

Weiguo Cao is a professor of biochemistry in the College of Science and a collaborative investigator for the grant.
Image Credit: Jim Melvin / Clemson University

“How do healthy individuals — many of whom are overweight — naturally prevent these proteins from aggregating? From this, we can learn the mechanisms. Then we can design therapeutics to mimic or promote these mechanisms,” Ding said. “The second topic is to look at how the small molecules, the naturally occurring polyphenols, help prevent aggregation. From this, we can design better inhibitors. The third topic is engineering nano-sized objects that can be used as drug carriers and also increase the efficacy of the drug.”

A slew of other diseases, including Alzheimer’s, Huntington’s, Lou Gehrig’s and Parkinson’s, might also be caused by similar forms of protein aggregation. For instance, people with Type 2 diabetes have much higher incidences of Alzheimer’s than occur in the general population. So the results of Ding and Cao’s research could potentially produce a menagerie of treatments.

“All these aggregation diseases look similar in that the molecular damage is caused by either the elongated protein fibrils or intermediate smaller aggregates that have become stuck together,” Ding said. “So this indicates that there might be an underlying commonality. In fact, some people are starting to call Alzheimer’s ‘Type 3 diabetes.’ “

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The grant is titled “Inhibition of Human Islet Amyloid Polypeptide Aggregation” and is sponsored by the National Institute of General Medical Sciences (NIGMS) under the Maximizing Investigators’ Research Award. MIRA grants encourage investigators to be flexible in their research, allowing them to veer from their original proposals based on their discoveries and the direction of their research. Additional collaborators for the grant include the Convergent Bio-Nano Science and Technology Center at Monash University in Australia and the St. Vincent’s Institute of Medical Research in Victoria, Australia.

Research reported in this publication was supported by the NIGMS of the National Institutes of Health (NIH) under Award Number R35GM119691. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.