Lopez Hender, Lobaskin Vladimir
Complex and Adaptive Systems Laboratory, School of Physics, University College Dublin, Belfield, Dublin 4, Ireland.
J Chem Phys. 2015 Dec 28;143(24):243138. doi: 10.1063/1.4936908.
We present a coarse-grained model for evaluation of interactions of globular proteins with nanoparticles (NPs). The protein molecules are represented by one bead per aminoacid and the nanoparticle by a homogeneous sphere that interacts with the aminoacids via a central force that depends on the nanoparticle size. The proposed methodology is used to predict the adsorption energies for six common human blood plasma proteins on hydrophobic charged or neutral nanoparticles of different sizes as well as the preferred orientation of the molecules upon adsorption. Our approach allows one to rank the proteins by their binding affinity to the nanoparticle, which can be used for predicting the composition of the NP-protein corona. The predicted ranking is in good agreement with known experimental data for protein adsorption on surfaces.
我们提出了一种粗粒度模型，用于评估球状蛋白质与纳米颗粒（NP）之间的相互作用。蛋白质分子由每个氨基酸一个珠子表示，纳米颗粒由一个均匀球体表示，该球体通过取决于纳米颗粒大小的中心力与氨基酸相互作用。所提出的方法用于预测六种常见人类血浆蛋白在不同大小的疏水带电或中性纳米颗粒上的吸附能，以及吸附时分子的优先取向。我们的方法允许人们根据蛋白质与纳米颗粒的结合亲和力对蛋白质进行排名，这可用于预测NP-蛋白质冠层的组成。预测的排名与蛋白质在表面吸附的已知实验数据高度一致。
