Models of the role of α-synuclein (α-syn) in Parkinson’s disease (PD) and the folding/aggregation properties of α-syn. (A) Alpha-syn is a critical player in the pathogenesis of PD and the loss-of-function hypothesis posits that as the disease progresses the pool of functional α-syn is depleted via aggregation (in the aggregation phase). The neurons in which α-syn is being reduced succumb to death once the pool of biologically functional α-syn is depleted past a certain threshold (green dashed line). Numerous insults that are intrinsic (e.g. mutant α-syn, abnormal α-syn modifications, oxidative stress, etc.) or extrinsic (e.g. environmental toxins, neuroinflammation, etc.) to the neurons can augment the process quickening the progression of the disease (gray line). (B) The structure and aggregation profile of α-syn is relatively complex. Under normal conditions, α-syn exist as a disordered monomer or in a stable tetramer. Interestingly, the formation of tetramers in vitro is less favorable than the formation of aggregates (green line), but in vivo α-syn may primarily exist in the tetrameric form (yellow-green line). This suggests two possibilities. 1) The in vitro conditions are not representative of in vivo conditions, and/or 2) there are unknown factors (Factor “X”) that facilitate the formation of tetramers in vivo (e.g. chaperones). If tetramers are dissociated they are more likely to form aggregates (dashed red arrows) than they are to reform tetramers. Disease-associated mutations of α-syn impede the formation of tetramers, and favor the formation of aggregates. The aggregation pathway is characterized by the progressive formation of soluble oligomers, protofibrils and mature fibrils (red line). Mutant forms of α-syn reduce the energy barrier for the formation of oligomers; and thus, favor the formation of fibrils (orange line). One important caveat with these models is that they tend to simplify a complicated process and make some generalizations that do not fit all of the current data. With that in mind, it is important to view these models with the understanding that they can, and should, be modified as more data become available.