Adhesive dynamics

• Published in: Journal of biomechanical engineering Vol. 136; no. 2; p. 021006
• Main Author: Hammer, Daniel A
• Format: Journal Article
• Language: English
• Published: United States 01.02.2014
• Subjects: Animals; Cell Adhesion - physiology; Cell Adhesion Molecules - metabolism; Cell Membrane - physiology; Cell Movement - physiology; Humans; Leukocytes - physiology; Mechanotransduction, Cellular - physiology; Models, Biological; Stress, Mechanical
• ISSN: 1528-8951
• DOI: 10.1115/1.4026402

Adhesive dynamics (AD) is a method for simulating the dynamic response of biological systems in response to force. Biological bonds are mechanical entities that exert force under strain, and applying forces to biological bonds modulates their rate of dissociation. Since small numbers of events usually control biological interactions, we developed a simple method for sampling probability distributions for the formation or failure of individual bonds. This method allows a simple coupling between force and strain and kinetics, while capturing the stochastic response of biological systems. Biological bonds are dynamically reconfigured in response to applied mechanical stresses, and a detailed spatio-temporal map of molecules and the forces they exert emerges from AD. The shape or motion of materials bearing the molecules is easily calculated from a mechanical energy balance provided the rheology of the material is known. AD was originally used to simulate the dynamics of adhesion of leukocytes under flow, but new advances have allowed the method to be extended to many other applications, including but not limited to the binding of viruses to surface, the clustering of adhesion molecules driven by stiff substrates, and the effect of cell-cell interaction on cell capture and rolling dynamics. The technique has also been applied to applications outside of biology. A particular exciting recent development is the combination of signaling with AD (so-called integrated signaling adhesive dynamics, or ISAD), which allows facile integration of signaling networks with mechanical models of cell adhesion and motility. Potential opportunities in applying AD are summarized.