Abstract
The Blood-Brain Barrier (BBB) is a physical and biochemical barrier that restricts the entry of certain drugs to the Central Nervous System (CNS), while allowing the passage of others. The ability to predict the permeability of a given molecule through the BBB is a key aspect in CNS drug discovery and development, since neurotherapeutic agents with molecular targets in the CNS should be able to cross the BBB, whereas peripherally acting agents should not, to minimize the risk of CNS adverse effects. In this review we examine and discuss QSAR approaches and current availability of experimental data for the construction of BBB permeability predictive models, focusing on the modeling of the biorelevant parameter unbound partitioning coefficient (Kp,uu). Emphasis is made on two possible strategies to overcome the current limitations of in silico models: considering the prediction of brain penetration as a multifactorial problem, and increasing experimental datasets through accurate and standardized experimental techniques.
Keywords: Blood-Brain Barrier, Brain Penetration, Central Nervous System, In Silico Models, Microdialysis, Passive Difussion, Pharmacokinetic, Protein Binding, QSAR Models, Unbound Drug Fraction.
Mini-Reviews in Medicinal Chemistry
Title:Current State and Future Perspectives in QSAR Models to Predict Blood- Brain Barrier Penetration in Central Nervous System Drug R&D
Volume: 17 Issue: 3
Author(s): Juan F. Morales, Sebastian Scioli Montoto, Pietro Fagiolino and Maria E. Ruiz
Affiliation:
Keywords: Blood-Brain Barrier, Brain Penetration, Central Nervous System, In Silico Models, Microdialysis, Passive Difussion, Pharmacokinetic, Protein Binding, QSAR Models, Unbound Drug Fraction.
Abstract: The Blood-Brain Barrier (BBB) is a physical and biochemical barrier that restricts the entry of certain drugs to the Central Nervous System (CNS), while allowing the passage of others. The ability to predict the permeability of a given molecule through the BBB is a key aspect in CNS drug discovery and development, since neurotherapeutic agents with molecular targets in the CNS should be able to cross the BBB, whereas peripherally acting agents should not, to minimize the risk of CNS adverse effects. In this review we examine and discuss QSAR approaches and current availability of experimental data for the construction of BBB permeability predictive models, focusing on the modeling of the biorelevant parameter unbound partitioning coefficient (Kp,uu). Emphasis is made on two possible strategies to overcome the current limitations of in silico models: considering the prediction of brain penetration as a multifactorial problem, and increasing experimental datasets through accurate and standardized experimental techniques.
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Cite this article as:
Morales F. Juan, Montoto Scioli Sebastian, Fagiolino Pietro and Ruiz E. Maria, Current State and Future Perspectives in QSAR Models to Predict Blood- Brain Barrier Penetration in Central Nervous System Drug R&D, Mini-Reviews in Medicinal Chemistry 2017; 17 (3) . https://dx.doi.org/10.2174/1389557516666161013110813
DOI https://dx.doi.org/10.2174/1389557516666161013110813 |
Print ISSN 1389-5575 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5607 |
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