Limited Time Offer

Claim a 25% discount on all eLearning courses (including credentials) with code ELEARN25.

Offer is valid from March 10-31. Public courses excluded from promo. 

(712h) Identifying Key Interactions in Amylin Self-Assembly Via Discontinuous Molecular Dynamics

Amyloid plaques are a hallmark of many protein misfolding diseases, including type 2 diabetes mellitus (T2D). Amylin is a 37 amino acid peptide hormone co-secreted with insulin. Aggregates of amylin peptides have been found in the pancreas of patients diagnosed with T2D. The insoluble aggregates build up into cytotoxic amyloid deposits, which lead to beta-cell death and loss of insulin production. Although T2D remains a common ailment in our population, much is left to be discovered about how these toxic aggregates form.

Our research objective is to investigate the assembly pathway of amylin peptides. We simulated a system of 50 amylin peptides starting from a random coil conformation using discontinuous molecular dynamics (DMD) in conjunction with the PRIME20 force field. DMD is an event-based simulation method in which molecules interact via discontinuous potentials. It is used in conjunction with PRIME20, an intermediate-resolution coarse-grained force field that models each amino acid with four spheres: three for the backbone (NH, CA, CO) and one for the sidechain group (R). Our simulation method has been used as a predictive tool to determine aggregation mechanisms for homotypic (single component) and heterotypic (multicomponent) assembly (e.g. Abeta, polyalanine, prion protein peptides (PrP(120 –144)), and CATCH peptides). The combination of DMD and PRIME20 allows us to characterize the assembly of amylin peptide aggregates on a microsecond timescale within a wall-clock time of a few weeks.

Simulation results have identified key interactions and oligomer intermediates formed during self-assembly. We find that amylin peptides assemble into parallel beta-sheet structures with a hinge, in agreement with experimental evidence. The amylin peptides tend to first form hydrogen bonds at residues 20-29, the structure then undergoes a conformation change to a fibril structure. Our simulation method affords us the ability to identify oligomeric intermediates that form before assembling into the final fibril structure. Intermediates and fibril formation are driven and stabilized by hydrophobic interactions and hydrogen bond formation. As far as we are aware, our work is the first to simulate full-length amylin peptides at this scale and resolution starting from random coil structures rather than from a structure obtained via crystallization. Knowledge of amylin’s assembly mechanism may help guide future studies of how to inhibit the fibrillation of other disease-related peptides such as Aβ (in Alzheimer’s disease) and α-synuclein (in Parkinson’s disease) .