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Modeling Nanoparticle Targeting to a Vascular Surface in Shear Flow Through Diffusive Particle Dynamics

机译:通过扩散粒子动力学模拟靶向剪切流中的血管表面的纳米粒子

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摘要

Nanoparticles are regarded as promising carriers for targeted drug delivery and imaging probes. A fundamental understanding of the dynamics of polymeric nanoparticle targeting to receptor-coated vascular surfaces is therefore of great importance to enhance the design of nanoparticles toward improving binding ability. Although the effects of particle size and shear flow on the binding of nanoparticles to a vessel wall have been studied at the particulate level, a computational model to investigate the details of the binding process at the molecular level has not been developed. In this research, dissipative particle dynamics simulations are used to study nanoparticles with diameters of several nanometers binding to receptors on vascular surfaces under shear flow. Interestingly, shear flow velocities ranging from 0 to 2000 s−1 had no effect on the attachment process of nanoparticles very close to the capillary wall. Increased binding energy between the ligands and wall caused a corresponding linear increase in bonding ability. Our simulations also indicated that larger nanoparticles and those of rod shape with a higher aspect ratio have better binding ability than those of smaller size or rounder shape.
机译:纳米颗粒被认为是用于靶向药物递送和成像探针的有希望的载体。因此,对靶向于受体涂覆的血管表面的聚合物纳米颗粒的动力学的基本理解对于增强纳米颗粒的设计以提高结合能力非常重要。尽管已在颗粒水平研究了粒径和剪切流对纳米颗粒与血管壁结合的影响,但尚未开发用于研究分子水平结合过程细节的计算模型。在这项研究中,耗散粒子动力学模拟用于研究在剪切流作用下与血管表面受体结合的直径为几纳米的纳米粒子。有趣的是,0到2000 s -1 范围内的剪切流速度对非常接近毛细管壁的纳米颗粒的附着过程没有影响。配体与壁之间增加的结合能导致结合能力相应线性增加。我们的模拟结果还表明,较大的纳米颗粒和长径比较大的棒状纳米颗粒比较小或较圆的形状具有更好的结合能力。

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