Perineuronal nets restrict transport near the neuron surface: A coarse-grained molecular dynamics study - Hanssen, Kine Ødegård; Malthe-Sørenssen, Anders (Frontiers in Computational Neuroscience, 2022)
Perineuronal nets (PNNs) are mesh-like extracellular matrix structures that wrap around certain neurons in the central nervous system. They are hypothesized to stabilize memories in the brain and act as a barrier between cell and extracellular space. The PNN components include long negatively charged linear sugar molecules. As a means to study the impact of PNNs on diffusion, the nets were approximated by negatively charged polymer brushes and simulated by coarse-grained molecular dynamics. Diffusion constants of single neutral and single charged particles were obtained in directions parallel and perpendicular to the brush substrate. The results for the neutral particle were compared to different theories of diffusion. A random walk lattice model from the literature was generalized and provided an acceptable fit in directions parallel to the brush substrate. A power law yielded the best fit in the perpendicular direction. The ratio of the perpendicular to parallel diffusion constants displayed a power law decay as a function of brush spacing. For a 50 nm thick brush, a diffusion time of up to 18 ns was obtained for smaller particles. The resistance of the brush was found from the diffusion of the charged particles and proved small compared to typical values of the membrane resistance of a neuron.