Multi-Scale Modelling Of the Formation of the Nanoparticle-Protein Corona

Extended Abstract A nanoparticle (NP) immersed in a biological medium does not remain in its native state for long, but instead rapidly acquires a corona of adsorbed proteins. This protein corona masks the original physical and chemical properties of the NP and is known to determine its biological fate, uptake by cells, and potential adverse outcomes [1]. Thus, the prediction of the corona content is crucial for the evaluation of the safety of novel biomaterials to avoid the requirement of experimentally investigating each of the large number of these biomaterials being introduced to the market. A given medium may consist of hundreds of proteins with the corona evolving over the course of several hours. With current computational tools, the simulation of the interaction between a single protein with an NP at an atomistic scale of accuracy is limited to at most a few nanoseconds of time and so clearly an alternate approach is necessary. The vast majority of proteins consist of only the twenty standard amino acids (AAs), suggesting that it should be possible to pre-compute these NP-AA interactions and use these to construct a model for the interaction of the entire protein with the NP, significantly simplifying the task of predicting the affinity of a given protein to the NP in question. Further coarse-graining of the system can then allow for modelling of the long-term adsorption and desorption of proteins, enabling the prediction of the content of the corona. Here,