School of Mechanical and Materials Engineering, Washington State University, Pullman, WA 99164-2920, United States.
School of Mechanical and Materials Engineering, Washington State University, Pullman, WA 99164-2920, United States.
Biochim Biophys Acta Gen Subj. 2018 Sep;1862(9):2104-2111. doi: 10.1016/j.bbagen.2018.06.018. Epub 2018 Jun 28.
Receptor dependent clathrin-mediated endocytosis (CME) is one of the most important endocytic pathways for the internalization of bioparticles into cells. During CME, the ligand-receptor interactions, development of clathrin-coated pit (CCP) and membrane evolution all act together to drive the internalization of bioparticles. In this work, we develop a stochastic computational model to investigate the CME based on the Metropolis Monte Carlo simulations.
The model is based on the combination of a stochastic particle binding model with a membrane model. The energetic costs of membrane bending, CCP formation and ligand-receptor interactions are systematically linked together.
We implement our model to investigate the effects of particle size, ligand density and membrane stiffness on the overall process of CME from the drug delivery perspectives. Consistent with some experiments, our results show that the intermediate particle size and ligand density favor the particle internalization. Moreover, our results show that it is easier for a particle to enter a cell with softer membrane.
The model presented here is able to provide mechanistic insights into CME and can be readily modified to include other important factors, such as actins. The predictions from the model will aid in the therapeutic design of intracellular/transcellular drug delivery and antiviral interventions.
受体依赖性网格蛋白包被的内吞作用(CME)是生物颗粒进入细胞内吞的最重要的内吞途径之一。在 CME 过程中,配体-受体相互作用、网格蛋白包被凹陷(CCP)的形成和膜的演化共同作用,驱动生物颗粒的内化。在这项工作中,我们基于 Metropolis 蒙特卡罗模拟开发了一个随机计算模型来研究 CME。
该模型基于随机粒子结合模型与膜模型的结合。膜弯曲、CCP 形成和配体-受体相互作用的能量成本被系统地联系在一起。
我们从药物输送的角度实施我们的模型来研究颗粒大小、配体密度和膜刚度对 CME 整体过程的影响。与一些实验一致,我们的结果表明,中间颗粒大小和配体密度有利于颗粒的内化。此外,我们的结果表明,对于较软的膜,颗粒更容易进入细胞。
这里提出的模型能够为 CME 提供机制上的见解,并可以很容易地修改为包括其他重要因素,如肌动蛋白。该模型的预测将有助于细胞内/跨细胞药物输送和抗病毒干预的治疗设计。