Shedding Light on the Dock-Lock Mechanism in Amyloid Fibril Growth Using Markov State Models

We investigate how the molecular mechanism of monomer addition to a growing amyloid fibril of the transthyretin TTR105-115 peptide is affected by pH. Using Markov state models to extract equilibrium and dynamical information from extensive all atom simulations allowed us to characterize both productive pathways in monomer addition as well as several off-pathway trapped states. We found that multiple pathways result in successful addition. All productive pathways are driven by the central hydrophobic residues in the peptide. Furthermore, we show that the slowest transitions in the system involve trapped configurations, that is, long-lived metastable states. These traps dominate the rate of fibril growth. Changing the pH essentially reweights the system, leading to clear differences in the relative importance of both productive paths and traps, yet retains the core mechanism.