Electrostatics controls the formation of amyloid superstructures in protein aggregation

TY - JOUR

T1 - Electrostatics controls the formation of amyloid superstructures in protein aggregation

AU - Foderà, Vito

AU - Zaccone, Alessio

AU - Lattuada, Marco

AU - Donald, Athene M.

PY - 2013/9/5

Y1 - 2013/9/5

N2 - The possibility for proteins to aggregate in different superstructures, i.e. large-scale polymorphism, has been widely observed, but an understanding of the physicochemical mechanisms behind it is still out of reach. Here we present a theoretical model for the description of a generic aggregate formed from an ensemble of charged proteins. The model predicts the formation of multifractal structures with the geometry of the growth determined by the electrostatic interactions between single proteins. The model predictions are successfully verified in comparison with experimental curves for aggregate growth allowing us to reveal the mechanism of formation of such complex structures. The model is general and is able to predict aggregate morphologies occurring both in vivo and in vitro. Our findings provide a framework where the physical interactions between single proteins, the aggregate morphology, and the growth kinetics are connected into a single model in agreement with the experimental data.

AB - The possibility for proteins to aggregate in different superstructures, i.e. large-scale polymorphism, has been widely observed, but an understanding of the physicochemical mechanisms behind it is still out of reach. Here we present a theoretical model for the description of a generic aggregate formed from an ensemble of charged proteins. The model predicts the formation of multifractal structures with the geometry of the growth determined by the electrostatic interactions between single proteins. The model predictions are successfully verified in comparison with experimental curves for aggregate growth allowing us to reveal the mechanism of formation of such complex structures. The model is general and is able to predict aggregate morphologies occurring both in vivo and in vitro. Our findings provide a framework where the physical interactions between single proteins, the aggregate morphology, and the growth kinetics are connected into a single model in agreement with the experimental data.

U2 - 10.1103/PhysRevLett.111.108105

DO - 10.1103/PhysRevLett.111.108105

M3 - Journal article

C2 - 25166715

SN - 0031-9007

VL - 111

JO - Physical Review Letters

JF - Physical Review Letters

IS - 10

M1 - 108105

ER -