Multi-scale modeling to predict ligand presentation within RGD nanopatterned hydrogels

Abstract

The adhesion ligand RGD has been coupled to various materials to be used as tissue culture matrices or cell transplantation vehicles, and recent studies indicate that nanopatterning RGD into high-density islands alters cell adhesion, proliferation, and differentiation. However, elucidating the impact of nanopattern parameters on cellular responses has been stymied by a lack of understanding of the actual ligand presentation within these systems. We have developed a multi-scale predictive modeling approach to characterize the adhesion ligand nanopatterns within an alginate hydrogel matrix. The models predict the distribution of ligand islands, the spacing between ligands within an island and the fraction of ligands accessible for cell binding. These model predictions can be used to select pattern parameter ranges for experiments on the effects of individual parameters on cellular responses. Additionally, our technique could also be applied to other polymer systems presenting peptides or other signaling molecules.