Effect of the air-water interface on the conformation of amyloid beta

Abstract

It has long been recognized that liquid interfaces, such as the air-water interface (AWI), can enhance the formation of protein fibrils. This makes liquid interfaces attractive templates for fibril formation but fully realizing this requires knowledge of protein behavior at interfaces, which is currently lacking. To address this, molecular dynamics simulation is used to investigate fragments of amyloid beta, a model fibril forming protein, at the air-water interface. At the air-water interface, the enrichment of aggregation-prone helical conformations provides a mechanism for the enhancement of fibrillation at interfaces. The conformational ensemble at the air-water interface was also considerably reduced compared to bulk solution due to the tendency of hydrophobic side chains partitioning into the air restricting the range of conformations. Little overlap between the conformational ensembles at the AWI and in the bulk solution was found, suggesting that AWI induces the formation of a different set of structures compared to bulk solution. The smaller Aβ(16-22) and Aβ(25-35) fragments show an increase in the propensity for an ordered secondary structure at the air-water interface but with a increased propensity for turn over other motifs, illustrating the importance of intra-protein interactions for stabilizing helical and extended conformations.

FIG. 1.

(a) Time variation of the secondary structure for A$\beta$(10–40) at the AWI (left) and in the bulk solution (right). $\alpha$-helix, $\beta$-strand, turn, 3/10-helix, and random coil (disordered) denoted by blue, yellow, red, cyan, and white, respectively. (b) Propensity for different secondary structure motifs (both ordered and random coil) for each residue (averaged over last 200 ns of simulations). $\alpha$-helix, $\beta$-strand, turn, 3/10-helix, and random coil (disordered) denoted by blue, yellow, red, cyan, and white, respectively.

FIG. 2.

Backbone hydrogen bond map for A$\beta$(10–40) at the AWI (left) and in the bulk solution (right).

FIG. 3.

A$\beta$(10–40) structure at the AWI. (a) Representative simulation snapshots, corresponding to the most common probable structures from cluster analysis. Hydrophobic side chains are highlighted as van der Waals (VDW) spheres. (b) Side chain orientation. Red, green, blue, and magenta denote hydrophobic, polar, negatively-charged, and positively charged residues, respectively. (c) Helical wheel plots for $\alpha$-helical regions (V12-D23 and A30-V36). Colors as in (b). (d) Probability histogram of helix orientation relative to AWI ($\cos \psi$).

FIG. 4.

(a) Probability of different clusters for A$\beta$(10–40) at the AWI (black) and in the bulk solution (red). (b) Snapshots showing higher ranked clusters for A$\beta$(10–40) at the AWI (left) and in the bulk solution (right).

FIG. 5.

Number of hydrogen bonds in clusters for A$\beta$(10–40) at the AWI (black) and in the bulk solution (red).

FIG. 6.

Probability of A$\beta$(10–40) solution conformations (by cluster ID) found in AWI simulation. Insets show snapshots of most probable solutionlike conformations at the AWI.

FIG. 7.

Secondary structure propensity for each residue (averaged over last 200 ns of simulations) at the AWI (left) and in the bulk solution (right). Top and bottom show A$\beta$(16–22) and A$\beta$(25–35), respectively. Colors as in Fig. 1.

FIG. 8.

Histogram of F19–F20 orientation for A$\beta$(16–22) (top) and A$\beta$(10–40) (bottom). AWI and solution data shown in black and red, respectively.

FIG. 9.

(a) Plot of scaling factor ($i$ denotes ${\beta }_i$) for A$\beta$(10–40) at the AWI. Graphs show (from top to bottom) replicas with $i=0$, 6, and 11 at $t=0$. (b) Plot of scaling factor ($i$ denotes ${\beta }_i$) for A$\beta$(10–40) in the bulk solution. Graphs show (from top to bottom) replicas with $i=0$, 5, and 9 at $t=0$.

FIG. 10.

Number of unique clusters against time for A$\beta$(10–40) at the AWI (black) and in the bulk solution (red). The main panel shows number of clusters within $3\mathrm{kcal}{\mathrm{mol}}^{-1}$ of most common cluster, and the inset shows the total number of clusters.