In Silico Cross Seeding of Aβ and Amylin Fibril-like Oligomers

Abstract

Recent epidemiological data have shown that patients suffering from Type 2 Diabetes Mellitus have an increased risk to develop Alzheimer's disease and vice versa. A possible explanation is the cross-sequence interaction between Aβ and amylin. Because the resulting amyloid oligomers are difficult to probe in experiments, we investigate stability and conformational changes of Aβ−amylin heteroassemblies through molecular dynamics simulations. We find that Aβ is a good template for the growth of amylin and vice versa. We see water molecules permeate the β-strand−turn−β-strand motif pore of the oligomers, supporting a commonly accepted mechanism for toxicity of β-rich amyloid oligomers. Aiming for a better understanding of the physical mechanisms of cross-seeding and cell toxicity of amylin and Aβ aggregates, our simulations also allow us to identify targets for the rational design of inhibitors against toxic fibril-like oligomers of Aβ and amylin oligomers.

On the lack of polymorphism in Aβ‐peptide aggregates derived from patient brains

“…The difference between the in vivo and in vitro fibril models also questions the relevance of previous computational studies that were based on the in vitro models and explored the effect of mutations, alternate fibril morphologies, or nucleation, in cross-seeding or for in silico structure-based search of inhibitors or imaging agents. [8][9][10][11][12] Our simulations indicate that the brain-derived model is less stable than the two in vitro models. The three-fold in vivo and in vitro fibril models are characterized by a central hydrated channel that may explain the toxicity of the amyloids as such channels interfere with nerve cells communication by changing membrane potential, and also may cause cell death because of loss of solutes.…”

“…6). 10 The average number of water molecules around each side-chain is shown in Figure 7 for both the in vivo model and the in vitro systems with three-fold symmetry. The presence of water in the central pore 22,26 observed in our molecular dynamics simulations suggests cell membrane leakage as a possible mechanism for oligomer-mediated toxicity.…”

Effect of single point mutations in a form of systemic amyloidosis

“…35 In Figure 1(A,B) we show the REI dimer, marking the location of the various mutations (R61, G68, D82, and A84) considered in this study. The two chains interact at two interfaces: the residues 41-46 in one unit, belonging to the loop (39-44) that connects the strands G and F and to strand F (45)(46)(47)(48)(49) interact with the loop (91-100) of the other unit, which connects the strands H and I. The residues R61 and D82 form a salt bridge and one can see that the residues D82 and A84 are close.…”

“…45,46 In a similar way, the pressure is kept constant at 1 bar by the Parrinello-Rahman algorithm (s 5 1 fs). 47,48 All models are initially minimized and equilibrated for 100 ps under NVT and then for 200 ps under NPT ensemble at 298.15 K. Measurements are then taken from a simulation of 100 ns under NVT conditions. For each system, three independent trajectories are simulated with a 2 fs time step, using different initial velocities.…”

Stability of Iowa mutant and wild type Aβ-peptide aggregates

“…46,47 In order to gain further insight into the relative stability of our four oligomers, we have done MM-PBSA calculations of the oligomers allowing us to monitor their interactions 48 through calculating approximate binding free energies from molecular simulations. 49,50 While the MM-PBSA approach in general does not replicate the absolute binding free energy values, 51 we chose this approach because it allows one to calculate quickly an estimate for differences in the free energy of binding, and because it usually exhibits a good correlation with experimental data. 52 In the present study, the binding energy between the two β-sheets (that is between the pentamers that form the decamer) is estimated with the MM-PBSA methodology as implemented in AMBER12.…”