Actin filaments impart cells with diverse functionalities such as their ability to move, divide, shape change, transport cargo, etc. This entire cellular machinery is driven by the polymerization, depolymerization, and nucleotide hydrolysis reactions of actin filaments leading to their dynamic remodeling and formation of higher-order structures. A complete understanding of the cooperative processes underlying the remodeling of actin filaments requires a multiscale approach capable of uniquely relating the conformational fluctuations of actin subunits with their reactions. In addition, it should also be able to represent the polymerization reactions in a computationally efficient manner due to their diffusion-limited characteristics arising from the extremely low cellular concentrations of actin monomers. Here, we combine two approaches, (i) Ultra-Coarse-Graining (UCG) [1-2] and (ii) Green Function Reaction Dynamics (GFRD) [3-4], to represent the reactions and diffusion of actin subunits, respectively. In the UCG method, the actin subunits are represented using explicit particles evolving in time using the Langevin dynamics. The reactions of the subunits are tied explicitly to their conformations using a Monte-Carlo state transition rule. In the GFRD approach, the actin subunits are represented at a mesoscale level and the Einstein’s diffusion equation is solved to propagate the randomly diffusing particle in time. The combined UCG-GFRD approach, therefore, offers a multiscale framework to efficiently study reactive-diffusive systems such as actin networks. Using this technique, specific results pertaining to the effects of external forces such as compressive and tensile strains on the actin network higher-order structure formation will be presented. Additionally, the effects of concentration will be investigated by studying the actin remodeling under strains at different concentrations of actin monomers. Broadly, the results will be useful to uncover the molecular pathways leading to actin remodeling under different conditions and will improve the overall understanding of this cellular machinery.
1) Dama, J. F.; Sinitskiy, A. V.; McCullagh, M.; Weare, J.; Roux, B.; Dinner, A. R.; Voth, G. A. The Theory of Ultra-Coarse-Graining. 1. General Principles. Journal of Chemical Theory and Computation 2013, 9, 2466-2480.
2) Davtyan, A.; Dama, J. F.; Sinitskiy, A. V.; Voth, G. A. The Theory of Ultra-Coarse-Graining. 2. Numerical Implementation. Journal of Chemical Theory and Computation 2014, 10, 5265-5275.
3) Vijaykumar, A.; Bolhuis, P. G.; Wolde, P. R. t. Combining molecular dynamics with mesoscopic Green’s function reaction dynamics simulations. The Journal of Chemical Physics 2015, 143, 214102.
4) Zon, J. S. v.; Wolde, P. R. t. Green’s-function reaction dynamics: A particle-based approach for simulating biochemical networks in time and space. The Journal of Chemical Physics 2005, 123, 234910
