The biophysical chemistry of nanoparticle-biosystem interactions

越来越多的纳米粒子会发现自己在生物环境中，无论是有目的的还是偶然的。 上述研究计划将显着推进我们的知识的关键NP属性，可用于预测NP与生物系统，包括膜和蛋白质的相互作用。参数，如相对电荷，NP大小和表面化学，表面张力和溶液离子强度将是一个预测矩阵模型，我们将开发的元素。目前的模型对环境的影响的NP和NP在生物体中的分布不具备预测能力的NP分配到膜上和膜中。我们开发的模型将影响监管NP的政策决定，可以直接与我们的体内工作进行比较，并用于合理设计新的NP。此外，我们在多伦多拥有独特的能力，可以使用MC-FCCS测量分层高阶NP的组装动力学和平衡。这将提供以前不可用的数据和深入了解NP组装过程，并将产生新的理解NP-蛋白质电晕动力学，NP絮凝动力学和胶体不稳定动力学。

Increasingly NPs will find themselves in biological milieus, either purposefully or accidentally. The research program described above will significantly advance our knowledge of the critical NP properties that can be used to predict NP interactions with biosystems including membranes and proteins. Parameters such as relative charge, NP size and surface chemistry, surface tension, and solution ionic strength will be elements of a predictive matrix model that we will develop. Current models for environmental impact of NPs and NP distributions in organisms do not possess predictive capabilities for partitioning of NPs onto and into membranes. The models we develop will influence policy decisions on regulating NPs, can be directly compared with our in vivo work, and used to rationally design new NPs. Additionally, we have a unique capability in Toronto to measure the assembly kinetics and equilibria for hierarchical, higher-order NPs using MC-FCCS. This will provide previously unavailable data and insight into the NP assembly process and will generate new understanding of NP-protein corona dynamics, NP flocculation dynamics and colloid instability dynamics.