Mississippi State University researcher Shantia Yarahmadian has developed a mathematical model to investigate how copper and zinc influence amyloid-beta protein aggregation, offering a new computational framework to study Alzheimer’s disease mechanisms.
Mathematical Modeling of Protein Aggregation
Biological phenomena occur in physical space and time, involving changes in shape, quantity, and matter. To capture these dynamics for research, Yarahmadian constructed a mathematical framework simulating the chemical reactions that occur when electrically charged metal ions interact with amyloid-beta proteins.
Amyloid-beta proteins can stick together in a process known as aggregation. Eventually, these groupings can help build up plaques, which represent a defining hallmark of Alzheimer’s disease.
The model examines how metal ions influence this protein buildup. Furthermore, it enables researchers to explore two potential therapeutic approaches designed to interfere with aggregation.
“Every biological phenomenon occurs in the physical world — in space and time — and involves changes in shape, quantity and matter,” Yarahmadian said.
“Because of its abstract power, mathematics allows us to uncover patterns, test hypotheses and make predictions that may not be possible through observation alone.”
Validating Simulations with Atomic Force Microscopy
A mathematical model is most useful when its predictions reflect what happens in actual experiments. To assess his model, Yarahmadian and his team benchmarked its outputs against physical data gathered via atomic force microscopy.
This microscope relies on a microscopic stylus to scan nanoscale structures, enabling scientists to analyze minuscule aggregations of proteins and other substances. The mathematical model successfully reproduced the patterns observed in the experiments.
This consistency indicates that the model accurately reflects key mechanisms of amyloid-beta clustering under the tested conditions. While these discoveries do not provide a working cure for Alzheimer’s, they provide a valuable instrument for directing upcoming bench experiments.
“Mathematics does not replace laboratory or clinical research; it complements it by helping us understand the larger system, identify the most influential mechanisms and guide future experiments,” Yarahmadian noted.
The Path Forward for Alzheimer’s Research
Investigating Alzheimer’s disease involves numerous interacting biological processes that are difficult to study individually. Mathematical modeling allows scientists to explore complicated biological interactions by representing them through equations and simulations.
Appearing in the Bulletin of Mathematical Biology, the study extends his continuous work applying quantitative methods to gain deeper insight into the intricate biological mechanisms driving Alzheimer’s.
“What drew me to Alzheimer’s research is the combination of its profound human impact and its extraordinary biological complexity,” Yarahmadian said. “My goal is to use mathematical modeling to identify important mechanisms and generate insights that may help guide future experimental and therapeutic research.”
