Blood–brain barrier permeability in Parkinson’s disease patients with and without dyskinesia

Author(s):  
Koji Fujita ◽  
Shichun Peng ◽  
Yilong Ma ◽  
Chris C. Tang ◽  
Matthew Hellman ◽  
...  
Author(s):  
Shee Man Voon ◽  
Khuen Yen Ng ◽  
Soi Moi Chye ◽  
Anna Pick Kiong Ling ◽  
Kenny Gah Leong Voon ◽  
...  

: 1-Methyl-1,2,3,4-tetrahydroisoquinoline-6,7-diol, commonly known as salsolinol, is a compound derived from dopamine. It was first discovered in 1973 and has gained attention for its role in Parkinson’s disease. Salsolinol and its derivatives were claimed to play a role in the pathogenesis of Parkinson’s disease as a neurotoxin that induces apoptosis of dopaminergic neurons due to its structural similarity to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and its ability to induce Parkinsonism. In this article, we discussed the biosynthesis, distribution and blood brain barrier permeability of salsolinol. The roles of salsolinol in healthy brain, particularly the interactions with enzymes, hormone and catecholamine were reviewed. Finally, we discussed the involvement of salsolinol and its derivatives in the pathogenesis of Parkinson’s disease.


2018 ◽  
Vol 25 (9) ◽  
pp. 1073-1089 ◽  
Author(s):  
Santiago Vilar ◽  
Eduardo Sobarzo-Sanchez ◽  
Lourdes Santana ◽  
Eugenio Uriarte

Background: Blood-brain barrier transport is an important process to be considered in drug candidates. The blood-brain barrier protects the brain from toxicological agents and, therefore, also establishes a restrictive mechanism for the delivery of drugs into the brain. Although there are different and complex mechanisms implicated in drug transport, in this review we focused on the prediction of passive diffusion through the blood-brain barrier. Methods: We elaborated on ligand-based and structure-based models that have been described to predict the blood-brain barrier permeability. Results: Multiple 2D and 3D QSPR/QSAR models and integrative approaches have been published to establish quantitative and qualitative relationships with the blood-brain barrier permeability. We explained different types of descriptors that correlate with passive diffusion along with data analysis methods. Moreover, we discussed the applicability of other types of molecular structure-based simulations, such as molecular dynamics, and their implications in the prediction of passive diffusion. Challenges and limitations of experimental measurements of permeability and in silico predictive methods were also described. Conclusion: Improvements in the prediction of blood-brain barrier permeability from different types of in silico models are crucial to optimize the process of Central Nervous System drug discovery and development.


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