S2: Protein Corona - Nanoparticle

How the Protein Corona Evolves on a Nanoparticle

S2: Protein Corona - Nanoparticle, OpenTox Euro 2017
PRESENTING AUTHOR: 

Giancarlo Franzese

INSTITUTION / COMPANY : 

University Barcelona

AUTHOR(S): 

[1] P. Vilaseca, K. A. Dawson, G. Franzese, Soft Matter 9, 6978−6985 (2013). [2] O. Vilanova, V. Bianco, G. Franzese, Multi-scale approach for self-assembly and protein folding, in "Design of self-assembling materials'', ed. I. Coluzza (Springer Publishing, New York), 2017. [3] O. Vilanova, J. J. Mittag, P. M. Kelly, S. Milani, K. A. Dawson, J. O. Rädler, G. Franzese, ACS Nano 10, 10842−10850 (2016). [4] The authors acknowledge funding from the EU FP7 NanoTransKinetics project grant NMP4- SL-2011-266737 and the Spanish MINECO Grants No. FIS2012-31025 and No. FIS2015-66879-C2-2-P.

ABSTRACT CONTENT / DETAILS: 

When a pristine nanoparticle (NP) encounters a biological fluid, biomolecules spontaneously form adsorption layers around the NP, called “protein corona”.  The corona composition depends on the time-dependent environmental conditions and determines the NP’s fate within living organisms. Understanding how the corona evolves is fundamental in nanotoxicology as well as medical applications. However, the process of corona formation is challenging due to the large number of molecules involved and to the large span of relevant time scales ranging from 100 μs, hard to probe in experiments, to hours, out of reach of all-atoms simulations. Here we combine experiments, simulations, and theory to study (i) the corona kinetics  (over 10−3−103 s) and (ii) its final composition for silica NPs in a model plasma made of three blood proteins (human serum albumin, transferrin, and fibrinogen). When computer simulations [1,2] are calibrated by experimental protein−NP binding affinities measured in single-protein solutions, the theoretical model correctly reproduces competitive protein replacement as proven by independent experiments. When we change the order of administration of the three proteins, we observe a memory effect in the final corona composition that we can explain within our model. Our combined experimental and computational approach is a step toward the development of systematic prediction and control of protein−NP corona composition based on a hierarchy of equilibrium protein binding constants [3,4].

 

 

Figure 1.  Kinetics of competing proteins (human serum albumin, transferrin and fibrinogen) assembling onto a silica NP of 100nm diameter. Simulation snapshots at three different times: 1st when introducing albumin; 2nd when adding transferrin; 3rd when adding fibrinogen.