Dissipative particle dynamics simulations for biological systems: From protein structures to cell mechanics

Abstract

<p indent="0mm">Dissipative particle dynamics (DPD) is a mesoscopic coarse-grained simulation method developed in recent years, which is an important method for studying the dynamic behaviors of soft matter and complex fluids. In this method, each DPD particle represents a coarse-grained virtual cluster of a set of atoms or groups of matter. The position and momentum of the DPD particle are updated in a continuous phase but spaced at discrete time steps. The coarse-grained DPD particles are subject to simplified pairwise interacting conservative, dissipative, and random forces. Especially, the dissipative force and random force in the DPD method act as a heat sink and a source, respectively, and the combined effect of these two forces act as a thermostat, which conserves momentum and thus provides the correct description of hydrodynamic interactions for the model system. In addition, a common choice of the soft repulsion for the conservative force allows using larger integration time steps in DPD simulations than that usually allowed in classical molecular dynamics (MD) simulations. Hence, compared with the MD method, the computational cost of the DPD simulation is significantly reduced due to the smaller number of modeled particles and the larger computational time step, enabling the simulations of the static and dynamic behaviors of complex fluids and soft matter systems at physically attractive length scale and time scale. Moreover, the particle-based framework of the DPD method enables people to easily incorporate additional physical features into the model systems and extend its application to complex systems. For these reasons, the DPD method and its extension have been successfully applied to numerous soft matter and complex fluid systems such as oil/water/surfactant systems, chemical morphology, microscopic morphology, phase separation, as well as dynamics and rheological properties of polymer solutions and colloidal suspensions. In this paper, we first introduce the theoretical formulation and parameterization of the DPD method. Then, we review recent advances in DPD modeling of biological systems, focusing on its applications at the molecular and cellular scales. At the molecular scale, we highlight examples of successful simulations of the protein structures and their interactions, the structure and dynamics of amphiphilic lipid molecule membranes (e.g., the self-assembly of lipid molecules, the structure and properties of lipid membranes, the fusion of lipid membranes, and the budding and fission of lipid membranes), the interaction of lipid membranes with protein molecules, and the interaction of nanoparticles with lipid membranes; at the cellular scale, we focus on the DPD modeling of blood cell flow and blood rheological behaviors in the blood microcirculatory systems, including the shape deformation and flow dynamics of red blood cells, the margination and adhesion dynamics of white blood cells, the margination and aggregation behaviors of platelets, the hemorheological behavior of blood flow, as well as the separation of circulating tumor cells from blood flow using microfluidic devices. Additionally, we compare the advantages and disadvantages of the microscale blood flow simulations between the continuum-based methods and particle-based methods, including the DPD method. Finally, we briefly present the development trends and application prospects of DPD modeling in biological systems.