CODES/Neural Network Model: a Useful Tool for in Silico Prediction of Oral Absorption and Blood-Brain Barrier Permeability of Structurally Diverse Drugs

2004 ◽  
Vol 23 (23) ◽  
pp. 89-98 ◽  
Author(s):  
Isabel Dorronsoro ◽  
Antonio Chana ◽  
Ma Inés Abasolo ◽  
Ana Castro ◽  
Carmen Gil ◽  
...  
Keyword(s):  
Neural Network ◽  
Blood Brain Barrier ◽  
Network Model ◽  
Neural Network Model ◽  
In Silico ◽  
Oral Absorption ◽  
In Silico Prediction ◽  
Barrier Permeability ◽  
Blood Brain Barrier Permeability ◽  
Brain Barrier Permeability

Ligand and Structure-based Modeling of Passive Diffusion through the Blood-Brain Barrier

2018 ◽  
Vol 25 (9) ◽  
pp. 1073-1089 ◽  
Author(s):  
Santiago Vilar ◽  
Eduardo Sobarzo-Sanchez ◽  
Lourdes Santana ◽  
Eugenio Uriarte
Keyword(s):  
Blood Brain Barrier ◽  
In Silico ◽  
Passive Diffusion ◽  
Brain Barrier ◽  
Barrier Permeability ◽  
Blood Brain Barrier Permeability ◽  
Blood Brain ◽  
Brain Barrier Permeability ◽  
Different Types ◽  
The Brain

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.

Synthesis, in silico and in vivo blood brain barrier permeability of ginkgolide B cinnamate

Fitoterapia ◽  
2015 ◽  
Vol 106 ◽  
pp. 110-114 ◽  
Author(s):  
Yong-Ming Lu ◽  
Jian Pan ◽  
Wen-Na Zhang ◽  
Ai-Ling Hui ◽  
Wen-Qiang Guo ◽  
...  
Keyword(s):  
Blood Brain Barrier ◽  
In Silico ◽  
Brain Barrier ◽  
Ginkgolide B ◽  
Barrier Permeability ◽  
Blood Brain Barrier Permeability ◽  
Blood Brain ◽  
Brain Barrier Permeability
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