A Systematic Review of Multiscale Mathematical Modelling of Cellular Mechan transduction Signalling: Methods, Architectures, and Future Research Directions

Abstract

Cellular mechanotransduction—the process by which cells convert mechanical stimuli into biochemical signals—plays a fundamental role in regulating cellular behavior, tissue development, and disease progression. Understanding this phenomenon requires integrative modeling frameworks capable of capturing interactions across multiple spatial and temporal scales, from molecular signaling networks to tissue-level mechanical responses. This systematic review presents a comprehensive analysis of multiscale mathematical models for mechanotransduction signaling. Advances in computational biology and applied mathematics have enabled frameworks that integrate mechanical deformation, intracellular signaling pathways, and extracellular matrix interactions. These models commonly combine continuum mechanics, reaction–diffusion systems, agent-based modeling, and stochastic simulations to describe the bidirectional coupling between mechanical forces and biochemical processes. Key signaling pathways such as Rho GTPase and YAP/TAZ are modeled using coupled reaction–diffusion and elasticity equations, illustrating how cell shape and substrate stiffness influence signaling dynamics. Multiscale approaches include hierarchical, concurrent, and hybrid frameworks, each balancing computational efficiency and biological realism. Emerging models also incorporate chemical–mechanical coupling to simulate tissue growth and morphogenesis. Despite progress, challenges remain in data integration, experimental validation, and computational complexity, though machine learning is improving predictive capabilities and simulation efficiency.