Abstract
Background: One of the underlying mechanisms of Parkinson’s disease is the aggregation of α-synuclein proteins, including amyloids and Lewy bodies in the brain. Aim: To study the inhibitory effect of doped carbon nanotubes (CNTs) on amyloid aggregation. Materials & methods: Molecular dynamics tools were utilized to simulate the influence of CNTs doped with phosphorus, nitrogen and bromine and nitrogen on the formation of α-synuclein amyloid. Results: The CNTs exhibited strong interactions with α-synuclein, with phosphorus-doped CNTs having the most substantial interactions. Conclusion: Doped-CNTs, especially phosphorus-doped carbon nanotube could effectively prevent α-synuclein amyloid formation, thus, it could be considered as a potential treatment for Parkinson’s disease. However, further in vitro and clinical investigations are required.
Graphical abstract
Supplementary data
To view the supplementary data that accompany this paper please visit the journal website at: www.tandfonline.com/doi/suppl/10.2217/nnm-2020-0372
Author contributions
M Khedri, AM Jahromi, E Alimohammadi, R Maleki and A Nikzad conceived and designed the simulation; M Khedri and AM Jahromi carried out the simulations with, visualization of output data and analyzed the data. M Rezaian and AM Jahromi wrote the manuscript with support from R Maleki. N Rezaei interpreted the results. The research was supervised and directed by N Rezaei. Authors contributed to investigation, conceptualization, methodology, analysis and writing-review and editing.
Financial & competing interests disclosure
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
No writing assistance was utilized in the production of this manuscript.
Availability of data and materials
All data generated or analyzed during this study are included in this published article.
Acknowledgments
The authors acknowledged B Bastan for his support in review and editing. They appreciated MM Nematollahi, Ali Mohammadi and E Ghasemy for sharing in the editing of this work.