Mesoscale simulations of two model systems in biophysics: from red blood cells to DNAs

Abstract

Computational modeling has become increasingly important in biophysics, but the great challenge in numerical simulations due to the multiscale feature of biological systems limits the capability of modeling in making discoveries in biology. Innovative multiscale modeling approaches are desired to bridge different scales from nucleic acids and proteins to cells and tissues. Although all-atom molecular dynamics has been successfully applied in many microscale biological processes such as protein folding, it is still prohibitively expensive for studying macroscale problems such as biophysics of cells and tissues. On the other hand, continuum-based modeling has become a mature procedure for analysis and design in many engineering fields, but new insights for biological systems in the microscale are limited when molecular details are missing in continuum-based modeling. In this context, mesoscale modeling approaches such as Langevin dynamics, lattice Boltzmann method, and dissipative particle dynamics have become popular by simultaneously incorporating molecular interactions and long-range hydrodynamic interactions, providing insights to properties on longer time and length scales than molecular dynamics. In this review, we summarized several mesoscale simulation approaches for studying two model systems in biophysics: red blood cells (RBCs) and deoxyribonucleic acids (DNAs). The RBC is a model system for cell mechanics and biological membranes, while the DNA represents a model system for B Zhangli Peng

Assessment of coupled bilayer–cytoskeleton modelling strategy for red blood cell dynamics in flow

“…Each structure then has its own mesh, allowing for different kinematics to be considered. However, although these models have provided compelling arguments in their favour (Peng et al 2015a;Zhang et al 2015;Li, Lu & Peng 2018), they are not the most common approach.…”

“…We believe that a comparative study to characterise the impact of different RBC modelling strategies is justified for another important reason: the contribution of surface viscosity. The origin of this viscosity can be explained by several mechanisms, but its inclusion in simulations depends on the choice of membrane representation (Li, Vlahovska & Karniadakis 2013;Vlahovska, Barthes-Biesel & Misbah 2013;Yazdani & Bagchi 2013;Fedosov, Noguchi & Gompper 2014;Freund 2014;Gounley & Peng 2015;Peng et al 2015a;Prado et al 2015;Li et al 2018;Guglietta et al 2020;Tsubota 2021). For instance, the friction of the junction proteins in the lipid bilayer can lead to significant variation in the effective surface viscosity of the RBC.…”

“…However, although these models have provided compelling arguments in their favour (Peng et al. 2015 a ; Zhang et al. 2015; Li, Lu & Peng 2018), they are not the most common approach.…”

“…The origin of this viscosity can be explained by several mechanisms, but its inclusion in simulations depends on the choice of membrane representation (Li, Vlahovska & Karniadakis 2013; Vlahovska, Barthes-Biesel & Misbah 2013; Yazdani & Bagchi 2013; Fedosov, Noguchi & Gompper 2014; Freund 2014; Gounley & Peng 2015; Peng et al. 2015 a ; Prado et al. 2015; Li et al.…”