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Schmit, J.

Publications and source records attributed to Schmit, J..

2 recordsLinked to original sources

Structural defects in amyloid-β fibrils drive secondary nucleation

The nucleation of amyloid fibrils from monomeric protein, catalyzed by the surface of existing fibrils, is an important driver of many disorders such as Alzheimers and Parkinsons diseases. The structural basis of this secondary nucleation process, however, is poorly understood. Here, we ask whether secondary nucleation sites are found predominantly at rare growth defects: defects in the fibril core structure generated during their original assembly. We first demonstrate using the specific inhibitor of secondary nucleation, Brichos, that secondary nucleation sites on Alzheimers disease-associated fibrils composed of A{beta}40 and A{beta}42 peptides are rare compared to the number of protein molecules they contain. We then grow A{beta}40 fibrils under conditions designed to eliminate most growth defects while leaving the regular fibril morphology unchanged, and confirm the latter using cryo-electron microscopy. We measure both the ability of these annealed fibrils to promote secondary nucleation and the stoichiometry of their secondary nucleation sites, finding that both are greatly reduced as predicted. Re-analysis of published data for other proteins suggests that fibril growth defects that expose monomer planes or other structural units may also drive secondary nucleation generally, across most or all amyloids. These findings could unlock structure-based drug design of therapeutics that aim to halt amyloid disorders by inhibiting secondary nucleation sites.

biophysics↗

The dark side of amyloid aggregation: Exploring the productive and non-productive pathways with multi-scale modeling

Atomistic description of protein fibril formation has remained prohibitive due to the complexity and long timescales of the conformational search problem. Here, we develop a multi-scale approach that combines a large number of atomistic molecular dynamics simulations in explicit solvent to derive Markov State Models (MSMs) for simulation of fibril growth. The search for the in-registered fully bound fibril state is modeled as a random walk on a rugged 2D energy landscape along enumerated {beta}-sheet registry and hydrogen bonding states, whereas interconversions among nonspecific bound states and between nonspecific and hydrogen-bounded states are derived from kinetic clustering analysis. The reversible association/dissociation of an incoming peptide and overall growth kinetics are then computed from MSM trajectories. This approach is applied to derive a comprehensive description of fibril elongation of wild-type A{beta}16-22 and how it is modulated by phenylalanine to cyclohexane (CHA) mutations. The resulting models recapitulate the experimental observation that mutants CHA19 and CHA1920 accelerate fibril elongation, but have a relatively minor effect on the critical concentration for fibril growth. Importantly, the kinetic consequences of mutations arise from a complex perturbation of the network of productive and non-productive pathways of fibril grown. This is consistent with the expectation that non-functional states will not have evolved efficient folding pathways and, therefore, will require a random search of configuration space. This study highlights the importance of describing the complete energy landscape when studying the elongation mechanism and kinetics of protein fibrils.

biophysics↗