Molecular Dynamics of Amyloid [beta]-Protein Assembly under Oxidative Conditions and Short Peptides in Aqueous Solutions
Authors:   , Zhang Shuting , Urbanc Brigita 
Published: September 2021

Proteins perform a variety of functions in living cells. Characterization of protein structures and dynamics is of vital importance in understanding life activities. Molecular dynamics (MD) simulations can provide detailed insights of protein structures that experimental methods can't measure directly. However, the performance of MD simulations is always based on approximations and assumptions of some extent. The reliability of MD simulation results largely depends on the correctness and precision of these assumptions. Whether the assumptions are correct or not can be assessed by comparing MD simulation results and experimental results. Chapter 3 and 4 studies the formation of amyloid [beta]-protein (A[beta]) under cross-linking conditions. A[beta] can self-assemble into toxic oligomers that are associated with Alzheimer's disease (AD). It is an intrinsically disordered protein (IDP) that lacks stable native structures. Due to its disordered nature, existence of mixtures of oligomers of different sizes, and short lifetime of oligomers, structural characterization of A[beta] through classical experimental methods, such as NMR and X-ray crystallography, can be challenging. Cross-linking provides a method to experimentally study the self-assembly of A[beta], whereas the mechanism of cross-linking is not yet understood. DMD4B-HYDRA approach is a computational method combining discrete molecular dynamics (DMD), 4-bead protein model, and implicit solvent. This method has been applied to study the self-assembly of A[beta] without cross-linking. Chapter 3 extends DMD4B-HYDRA approach by allowing formation of cross-links and assumes tyrosine is the only amino acid residue in A[beta] that is able to form cross-links. However, the limited cross-linked oligomer sizes are inconsistent with oligomer size distributions from cross-linking experiments. In order to avoid the volume exclusion issue revealed by Chapter 3, Chapter 4 examines three possible cross-linking mechanisms involving different amino acids in addition to tyrosine. Among the three mechanisms, only the mechanism involving phenylalanine produced oligomer size distributions consistent with experimental results. Classical MD simulations apply force fields to determine the motion of atoms and molecules. Chapter 5 assesses six state-of-the-art MD force fields on alanine and glycine by a direct comparison to experimental results. For alanine, Amber ff14SB produces the MD-derived results closest to experimental results. Whereas for glycine, CHARMM36m outperforms Amber ff14SB and OPLS-AA/M. Chapter 6 extends the studies on GAG in Chapter 5 to study the effect of mixed solvent of ethanol and water. Simulations are first performed on a single GAG peptide. Despite Amber ff14SB best reproduces the experimental J coupling constants and VCD profile again, all three force fields examined (Amber ff14SB, OPLS-AA/M, and CHARMM36m) fail to capture the transition of mesostate. Further simulations on multiple GAG peptides (with peptide concentration of 200 mM) indicate that CHARMM36m is able to to capture the effect of ethanol on the average pPII content of alanine in GAG and provide a plausible explanation for this effect, which may stem from an increased propensity of GAG to form oligomers in the presence of ethanol.