耗散粒子动力学方法在生物学领域的应用与研究进展:从蛋白质结构到细胞力学

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

耗散粒子动力学(dissipative particle dynamics,DPD)是近年发展起来的一种介观尺度的数值模拟方法,是研究软物质和复杂流体动力学行为的一种重要手段.这种新型介观模拟方法采用粗粒化粒子模型描述具有关联性的原子团或物质团,并通过简单的软排斥作用力描述粗粒化粒子间的相互作用,从而实现更大时间和空间尺度的复杂系统模拟计算,如油/水/表面活性剂体系、聚合物和胶体溶液的化学形态、微观形貌、相分离以及复杂流体流变特性的模拟等.本文首先介绍了DPD方法的理论框架,继而详细综述了DPD方法在生物系统中的应用.具体地,在分子尺度,我们重点介绍了该方法在蛋白质结构及其相互作用、两亲性脂质分子膜的结构与动力学、脂质膜与蛋白分子相互作用、纳米颗粒与脂质膜相互作用等方面的研究现状和研究热点.在细胞尺度,我们归纳了DPD方法在模拟血液微循环系统中血细胞的流动和血液流变学行为等方面的应用进展,包括红细胞的变形及流动,白细胞边聚及黏附行为,血小板边聚、黏附及聚集行为,健康与疾病状态下血液流变学特征,循环肿瘤细胞迁移、黏附及分选富集等.此外,我们总结了用于模拟血细胞变形及血液流动的其他数值模型并进行了简单比较.最后,我们简单展望了DPD方法在生物学领域的发展趋势和应用前景.

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.