For the case of the smaller model systems, an additional g3 analysis was performed on the last 50 ns of each simulation (with 10 ps time steps). The procedure was developed by Sukhomlinov et al. and is described in more detail in a recent study by Davies et al. A radial-angular three-particle distribution function is used to create heatmaps from intra-residue angles and distances. For every time step and every selected atom 𝐵 of each monomer, the distance 𝑟 ⃗ 𝐵𝐶 to any other atom 𝐶 within the selection is computed, given an angle Ɵ 𝐴𝐵𝐶 between atoms 𝐴 (the nearest atom to 𝐶), 𝐵 and 𝐶 (see also Figure , top right). For this analysis, four atoms present within every monomer type were selected: the amide nitrogen and oxygen, in addition to the first sidechain carbon atom and the second backbone carbon atom of the respective residue. Termini of the hexamers were excluded and a distance cutoff of 6 Å was chosen. Generated heatmaps of all 12 different model systems were then combined into a single similarity matrix using mean structural similarity index metrics (SSIM). The Analogously to Davies et al., the generated similarity matrix was then reduced to a 2D dataset via tdistributed stochastic neighbor embedding (t-SNE) and subsequent density-based spatial clustering (DBScan). A perplexity of 50 was used for t-SNE and a minimum sample size of 25 monomers with a distance threshold 𝜀 of 0.25 was chosen. Finally, a principal component analysis (PCA) was performed to assess conformations of the different clusters. Thus, using the described g3 analysis method, monomers of all systems were effectively clustered according to differences in intra-residue angle and distance distributions.