Abstract
Background: Parkinson's disease (PD) is one of the most common neurodegenerative disorders. One of the underlying mechanisms of the disease is the accumulation of α-synuclein protein aggregates, including amyloids and Lewy bodies in the brain, resulting in the death of dopaminergic cells in the substantia nigra. The current treatments for PD are mainly focused on replacing dopamine. However, if these medications are stopped, the severity of PD will increase. Moreover, the drugs used for the treatment of PD are associated with considerable side effects and dietary restrictions. Therefore, necessary studies to develop more effective medications for PD seem to be indispensable. To prevent the progression of PD, avoiding the development of α-synuclein amyloids could be proposed. Methods: In this study, the effects of three last-generation nanotube-based structures on α-synuclein amyloid formation were investigated for the first time employing Molecular Dynamics (MD) simulation tools. Molecular dynamics provide a deep insight into atomic interactions and can well study α-synuclein amyloid formation at the atomic and molecular scales.Results: The molecular study results indicated that all of the nanotubes studied in this work, had strong energy interactions with α-synuclein. Therefore, nanotubes using phosphorus, nitrogen and boron dopants, have great potential to prevent α-synuclein amyloid formation. Among these nanotubes, phosphorus-doped carbon nanotube (P-CNT) has the most substantial interactions with α-synuclein. The P-CNT caused more hydrogen bonds to be formed between water and α-synuclein molecules. This phenomenon leads to a decrease in the compactness, stability, and contact area of α-synuclein proteins, which results in considerable changes in the secondary structure of α-synuclein.Conclusions: Doping nanotubes especially P-CNT could be very effective for preventing the α-synuclein amyloid formation and hence, halting the progression of PD. This molecular study paves the way for the use of the Doping nanotubes in the treatment of PD. These structures are highly tunable and flexible. Therefore, the results of this work can be developed to computational, experimental and clinical levels.
Multivariable clinical-genetic model for predicting dyskinesia in early-onset Parkinson’s disease
