Strukturbildung und Aggregation solvatisierter Peptide in Gegenwart gelöster Ionen

This project aims at providing a microscopic (atomistic) picture of the initial structural intermediates, which eventually lead to amyloid misfolding of proteins. We will employ computational methods with atomistic resolution ranging from quantum chemistry via first-principles molecular dynamics simulations up to force field based molecular dynamics simulations. This combination of methods is able to elucidate structural and dynamical details of molecular systems under realistic conditions (temperature, chemical environment) as well as their spectroscopic properties. This project will thus contribute a novel aspect to the research portfolio of the SFB/TRR 102, namely the extension of the length- and time-scales of structure formation down to the Ångstrom and picosecond range. The calculations will attempt a characterization of universal structural motifs in terms of the inter-chain hydrogen bond network of aggregated peptide chains (cross-b structures). The simulations will focus on the thermodynamically most relevant microstructures, and specific point mutations will reveal whether the observed hydrogen bonding (H-bonding) network pattern are universal or specific to particular residue sequences. In this context, the relevance of salt bridges and the influence of solvated ions on the structure and solvation abilities of liquid water will be investigated, especially in view of the induced perturbation of the peptide-peptide interactions. This approach will thus also yield a molecular understanding of the Hofmeister effect (chaotropic/kosmotropic characteristics) which can be seen as a simplified representation of biomolecular crowding by proteins and peptides.

The perspective of the project for the upcoming periods is the first-principles and force field based molecular dynamics simulation of the interactions between amyloidogene protein fragments in the presence of additional ions, which are intended to mimic the physiological environment of the proteins. In addition, this approach is able to partially represent the effect of biomolecular crowding.