Exploring the Interplay between Disordered and Ordered Oligomer Channels on the Aggregation Energy Landscapes of α-Synuclein

Abstract

The abnormal aggregation of α-synulcein is associated with multiple neurodegenerative diseases such as Parkinson’s disease. The hydrophobic non-amyloid component (NAC) region of α-synuclein comprises the core of the fibril in vitro and in vivo. In this work, we study the aggregation landscape of the hydrophobic NAC region of α-synuclein using a transferrable coarse-grained force field, the associative memory water-mediated structure, and energy model (AWSEM). Using structural similarity, we can group metastable states on the free energy landscape of aggregation into three types of oligomers: disordered oligomers, prefibrillar oligomers with disordered tips, and ordered prefibrillar oligomers. The prefibrillar oligomers with disordered tips have more in-register parallel β strands than do the fully disordered oligomers but have fewer in-register parallel β strands than the ordered prefibrillar oligomers. Along with the ordered prefibrillar species, the disordered oligomeric states dominate at small oligomer sizes while the prefibrillar species with disordered tips thermodynamically dominate with the growth of oligomers. The topology of the aggregation landscape and observations in simulations suggest there is backtracking between ordered prefibrillar oligomers and other kinds of oligomers as the aggregation proceeds. The significant structural differences between the ordered prefibrillar oligomers and the disordered oligomers support the idea that the growth of these two kinds of oligomers involves kinetically independent parallel pathways. In contrast, the overall structural similarity between the fully ordered prefibrillar oligomers and the prefibrillar oligomers with disordered tips implies that two channels can interconvert on slower time scales. We also evaluate the effects of phosphorylation on the aggregation free energy landscape using statistical mechanical perturbation theory.

Flanking regions, amyloid cores, and polymorphism: the potential interplay underlying structural diversity

“…Furthermore, these simulations were unable to clearly demarcate the energy barrier between the two populations suggesting easier interconversion. Additionally, the investigators also identified a stable nucleus size of two to three monomeric units for αSyn oligomers, which agrees well with experimental observations ( 249 , 250 , 251 , 252 ). Significant dissociation and reassociation events were also seen in the early oligomeric species, which potentially provide a route for transition and interconversion of distinct oligomeric forms ( 249 ).…”

“…The higher sensitivity of the low-FRET oligomers to environmental changes and proteolytic digestion also indirectly hints at the prevalence of structural disorder within these species. Support for these findings comes from computational modeling of αSyn aggregation which reveals that the energy landscape permits the presence of two distinct populations of αSyn: disordered oligomers with a weaker hydrogen bond network and prefibrillar oligomers which show an ordered assembly with numerous interchain, parallel hydrogen bonds ( 249 ). Furthermore, these simulations were unable to clearly demarcate the energy barrier between the two populations suggesting easier interconversion.…”

Neural potentials of proteins extrapolate beyond training data

“…[50] This FF has been successfully applied to study protein structure prediction. [83][84][85] lowest overall performance among all four FFs c) TorchMD-Net's performance is comparable among all four proteins regardless of the structural disorder.…”

Neural potentials of proteins extrapolate beyond training data

“…[42] This FF has been successfully applied to study protein structure prediction. [75][76][77] CG trajectories from forcefields FF0 from CGSchNet, TorchMD-Net, MARTINI and OpenAWSEM were featurized and projected into a FES using TICA. [30] Figure 3 show the cartoon representations of the 3 miniproteins along with their projected trajectories.…”