Contrasting Disease and Nondisease Protein Aggregation by Molecular Simulation

Abstract

CONSPECTUS Protein aggregation can be defined as the sacrifice of stabilizing intrachain contacts of the functional state that are replaced with interchain contacts to form non-functional states. The resulting aggregate morphologies range from amorphous structures without long-range order typical of nondisease proteins involved in inclusion bodies to highly structured fibril assemblies typical of amyloid disease proteins. In this Account, we describe the development and application of computational models for the investigation of nondisease and disease protein aggregation as illustrated for the proteins L and G and the Alzheimer’s Aβ systems. In each case, we validate the models against relevant experimental observables and then expand on the experimental window to better elucidate the link between molecular properties and aggregation outcomes. Our studies show that each class of protein exhibits distinct aggregation mechanisms that are dependent on protein sequence, protein concentration, and solution conditions. Nondisease proteins can have native structural elements in the denatured state ensemble or rapidly form early folding intermediates, which offers avenues of protection against aggregation even at relatively high concentrations. The possibility that early folding intermediates may be evolutionarily selected for their protective role against unwanted aggregation could be a useful strategy for reengineering sequences to slow aggregation and increase folding yield in industrial protein production. The observed oligomeric aggregates that we see for nondisease proteins L and G may represent the nuclei for larger aggregates, not just for large amorphous inclusion bodies, but potentially as the seeds of ordered fibrillar aggregates, since most nondisease proteins can form amyloid fibrils under conditions that destabilize the native state. By contrast, amyloidogenic protein sequences such as Aβ1–40,42 and the familial Alzheimer’s disease (FAD) mutants favor aggregation into ordered fibrils once the free-energy barrier for forming a critical nucleus is crossed. However, the structural characteristic and oligomer size of the soluble nucleation species have yet to be determined experimentally for any disease peptide sequence, and the molecular mechanism of polymerization that eventually delineates a mature fibril is unknown. This is in part due to the limited experimental access to very low peptide concentrations that are required to characterize these early aggregation events, providing an opportunity for theoretical studies to bridge the gap between the monomer and fibril end points and to develop testable hypotheses. Our model shows that Aβ1–40 requires as few as 6–10 monomer chains (depending on sequence) to begin manifesting the cross-β order that is a signature of formation of amyloid filaments or fibrils assessed in dye-binding kinetic assays. The richness of the oligomeric structures and viable filament and fibril polymorphs that we observe may offer structural clues to disease virulence variations that...

The culprit behind amyloid beta peptide related neurotoxicity in Alzheimer's disease: oligomer size or conformation?

“…Computational analysis of the fibrillation pathways of Aβ 1-40 and familial AD-related mutations suggests that early events involve the formation of an ordered, cross-β- structured nucleus composed of six to ten monomer chains [115]. This supports an earlier proposition by Grant and colleagues [116] that the aggregate seed for Aβ involves a specific type of collapsed structure involving exposed β-strands.…”

Principles governing oligomer formation in amyloidogenic peptides

“…Simulations using coarse-grained (CG) models [25, 53–55] have revealed that the formation of oligomers and subsequently fibrils involves a number of distinct stages during which the monomers, oligomers, and protofilaments undergo substantial conformational changes. Interestingly, it has been proposed the mutations that diminish β -strand propensity in the monomeric peptides may diminish fibril formation (by reducing population of N * ) while enhancing the formation of potentially toxic oligomeric structures[55].…”

“…While the dynamics and phase diagram of full length aggregating proteins are expected to be considerably richer, the aggregation tendencies of smaller peptides are excellent model systems, which can be used to gain quantitative biophysical insights into oligomer formation. In recent years, a combination of experimental [11, 17–20] and computational studies [13, 21–25] have led to a microscopic picture of the oligomerization process of peptides including the role water of in their self-assembly. In this perspective, we focus on the role molecular dynamics simulations have played in elucidating some of the general principles that govern the process of protein aggregation with particular emphasis on the initial events in the assembly of A β -peptides and their implications for the growth into mature amyloid-fibrils.…”

An implicit solvent coarse-grained lipid model with correct stress profile

“…This level of coarse-grain ͑CG͒ modeling has proved appropriate for protein folding studies, explaining why native sequences fold more rapidly and more reliably relative to poorly designed or arbitrary heteropolymer sequence, 4,5 qualitatively reproducing differences in folding kinetics of small and large proteins, 6 and have been used to clarify the role of native state topology and minimal energetic frustration in the determination of folding rate and mechanism. [7][8][9][10][11][12][13][14][15] A simplifying feature of these coarse-grained protein models has been the implicit treatment of the aqueous solvent environment, which is absorbed in the effective potentials among the bead residues, solvent frictional forces, and random collisions exerted on the moving chain described by Langevin dynamics.…”