In a recent study, researchers at Auburn University Dr. Marcelo Melo, in collaboration with Colorado State University Dr. Rafael Bernardi, have utilized artificial intelligence (AI) and molecular simulations to uncover the rapid activation of catch-bonds, a type of protein interaction that strengthens under mechanical force. This discovery enhances our understanding of protein resilience and opens new avenues in biomaterials and drug design.
C. R. Melo, M., & Bernardi, R. C. (2025). AI Uncovers the Rapid Activation of Catch-Bonds under Force. Journal of Chemical Theory and Computation. https://doi.org/10.1021/acs.jctc.5c01181
Catch-bonds are unique protein interactions that become stronger when subjected to mechanical stress, akin to the tightening of a Chinese finger trap. These bonds play a crucial role in various biological processes, including bacterial adhesion to host cells and the maintenance of tissue integrity under stress. However, the precise mechanisms governing their activation have remained unclear.
Dr. Bernardi, Associate Professor of Physics at Auburn University, stated,
“This told us that the proteins already ‘decide’ their level of resilience right after the pulling begins. The catch-bond mechanism is activated almost instantly.”
The research team focused on cellulosomes, complex protein structures known for their strong catch-bond properties. Employing steered molecular dynamics simulations, they generated high-resolution models of these proteins under stress. Subsequently, AI regression models were trained to predict the rupture points of these bonds. Remarkably, the AI models accurately forecasted bond failures using brief segments of simulation data, indicating that the proteins determine their resilience almost immediately upon the application of force.
This study underscores the potential of AI in analyzing dynamic biological systems. By identifying early indicators of protein stability, AI can aid in the design of biomaterials and therapeutic strategies that leverage mechanical forces. Understanding catch-bonds could lead to the development of more effective adhesives, drug delivery systems, and treatments for diseases where tissue integrity is compromised.
The integration of AI with molecular simulations represents a significant advancement in computational biophysics, offering deeper insights into the complex behaviors of proteins and their applications in medicine and materials science.
Adrian graduated with a Masters Degree (1st Class Honours) in Chemical Engineering from Chester University along with Harris. His master’s research aimed to develop a standardadised clean water oxygenation transfer procedure to test bubble diffusers that are currently used in the wastewater industry commercial market. He has also undergone placments in both US and China primarely focused within the R&D department and is an associate member of the Institute of Chemical Engineers (IChemE).
