Department of Chemistry, University of Michigan, Ann Arbor, MI, 48109, USA.
Department of Chemistry and Biophysics Program, University of Michigan, Ann Arbor, MI, 48109, USA.
Small. 2017 May;13(18). doi: 10.1002/smll.201603748. Epub 2017 Mar 7.
Understanding the fundamental biophysics behind protein-nanoparticle (NP) interactions is essential for the design and engineering bio-NP systems. The authors describe the development of a coarse-grained protein-NP model that utilizes a structure centric protein model. A key feature of the protein-NP model is the quantitative inclusion of the hydrophobic character of residues in the protein and their interactions with the NP surface. In addition, the curvature of the NP is taken into account, capturing the protein behavior on NPs of different size. The authors evaluate this model by comparison with experimental results for structure and adsorption of a model protein interacting with an NP. It is demonstrated that the simulation results recapitulate the structure of the small α/β protein GB1 on the NP for data from circular dichroism and fluorescence spectroscopy. In addition, the calculated protein adsorption free energy agrees well with the experimental value. The authors predict the dependence of protein folding on the NP size, surface chemistry, and temperature. The model has the potential to guide NP design efforts by predicting protein behavior on NP surfaces with various chemical properties and curvatures.
理解蛋白质-纳米颗粒（NP）相互作用背后的基本生物物理学对于设计和工程生物-NP 系统至关重要。作者描述了一种粗粒蛋白质-NP 模型的开发，该模型利用了以结构为中心的蛋白质模型。蛋白质-NP 模型的一个关键特征是定量包含蛋白质中残基的疏水性及其与 NP 表面的相互作用。此外，还考虑了 NP 的曲率，从而捕捉到了不同大小的 NP 上蛋白质的行为。作者通过将该模型与模型蛋白与 NP 相互作用的结构和吸附的实验结果进行比较来评估该模型。结果表明，模拟结果再现了小 α/β 蛋白 GB1 在 NP 上的结构，这与圆二色性和荧光光谱学的数据一致。此外，计算出的蛋白质吸附自由能与实验值吻合较好。作者预测了蛋白质折叠对 NP 尺寸、表面化学和温度的依赖性。该模型具有通过预测具有各种化学性质和曲率的 NP 表面上的蛋白质行为来指导 NP 设计工作的潜力。
