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Abstract We demonstrate the application of the transition manifold framework to the late-stage fibrillation process of the NFGAILS peptide, a amyloidogenic fragment of the human islet amyloid polypeptide (hIAPP). This framework formulates machine learning methods for the analysis of multi-scale stochastic systems from short, massively parallel molecular dynamical simulations. We identify key intermediate states and dominant pathways of the process. Furthermore, we identify the optimally timescale-preserving reaction coordinate for the dock-lock process to a fixed pre-formed fibril and show that it exhibits strong correlation with the mean native hydrogen-bond distance. These results pave the way for a comprehensive model reduction and multi-scale analysis of amyloid fibrillation processes. Graphic Abstract

The hexapeptide hIAPP22–27 (NFGAIL) is known as a crucial amyloid core sequence of the human islet amyloid polypeptide (hIAPP) whose aggregates can be used to better understand the wild‐type hIAPP′s toxicity to β‐cell death. In amyloid research, the role of hydrophobic and aromatic‐aromatic interactions as potential driving forces during the aggregation process is controversially discussed not only in case of NFGAIL, but also for amyloidogenic peptides in general. We have used halogenation of the aromatic residue as a strategy to modulate hydrophobic and aromatic‐aromatic interactions and prepared a library of NFGAIL variants containing fluorinated and iodinated phenylalanine analogues. We used thioflavin T staining, transmission electron microscopy (TEM) and small‐angle X‐ray scattering (SAXS) to study the impact of side‐chain halogenation on NFGAIL amyloid formation kinetics. Our data revealed a synergy between aggregation behavior and hydrophobicity of the phenylalanine residue. This study introduces systematic fluorination as a toolbox to further investigate the nature of the amyloid self‐assembly process., F for formation: This study introduces systematic fluorination as a tool to investigate the nature of amyloid formation as shown for the model peptide NFGAIL. Modulation of hydrophobicity and the σ‐framework of the Phe residue trough fluorine and iodine led to different amyloid folding kinetics. TEM and SAXS studies revealed the presence of amyloid fibrils.