A Novel Modeling and Simulation Approach for the Hindered Mobility of Charged Particles in Biological Hydrogels

TL;DR

This paper introduces a new computational model that simulates how charged particles move within biological hydrogels, considering fiber orientation, connectivity, and elastic deformation, to better understand filtering mechanisms.

Contribution

It is the first model to incorporate 3D fiber orientation, connectivity, and fiber elasticity in studying particle mobility in hydrogels, with novel formulations for electrostatic and steric interactions.

Findings

Fiber and charge distribution significantly affect particle mobility.

Distinct motion patterns emerge based on network charge agglomerations.

Model validation confirms its potential for predictive biological system analysis.

Abstract

This article presents a novel computational model to study the selective filtering of biological hydrogels due to the surface charge and size of diffusing particles. It is the first model that includes the random 3D fiber orientation and connectivity of the biopolymer network and that accounts for elastic deformations of the fibers by means of beam theory. As a key component of the model, novel formulations are proposed both for the electrostatic and repulsive steric interactions between a spherical particle and a beam. In addition to providing a thorough validation of the model, the presented computational studies yield new insights into the underlying mechanisms of hindered particle mobility, especially regarding the influence of the aforementioned aspects that are unique to this model. It is found that the precise distribution of fiber and thus charge agglomerations in the network have a crucial influence on the mobility of oppositely charged particles and gives rise to distinct motion patterns. Considering the high practical significance for instance with respect to targeted drug release or infection defense, the provided proof of concept motivates further advances of the model toward a truly predictive computational tool that allows a case- and patient-specific assessment for real (biological) systems.