title: Improving the prediction of drug disposition in the brain.
abstract: BACKGROUND
  Ability to cross the blood-brain barrier is one of the key ADME characteristics of all drug candidates regardless of their target location in the body. While good brain penetration is essential for CNS drugs, it may lead to serious side effects in case of peripherally-targeted molecules. Despite a high demand of computational methods for estimating brain transport early in drug discovery, achieving good prediction accuracy still remains a challenging task.
  
  
  METHODS
  This article reviews various measures employed to quantify brain delivery and recent advances in QSAR approaches for predicting these properties from the compound's structure. Additionally, the authors discuss the classification models attempting to distinguish between permeable and impermeable chemicals.
  
  
  CONCLUSIONS
  Recent research in the field of brain penetration modeling showed an increasing understanding of the processes involved in drug disposition, although most models of brain/plasma partitioning still rely on purely statistical considerations. Preferably, new models should incorporate mechanistic knowledge since it is the prerequisite for guiding drug design efforts in the desired direction. To increase the efficiency of computational tools, a broader view is necessary, involving rate and extent of brain penetration, as well as plasma and brain tissue binding strength, instead of relying on any single property.
authors.affiliation: VšĮ Aukštieji algoritmai, A. Mickeviciaus 29, LT-08117 Vilnius, Lithuania. kiril.lanevskij@aukstieji.lt
authors.forename: Kiril
authors.initials: K
authors.lastname: Lanevskij
authors.forename: Pranas
authors.initials: P
authors.lastname: Japertas
authors.forename: Remigijus
authors.initials: R
authors.lastname: Didziapetris
mesh_terms: D001812:Blood-Brain Barrier / Q000187:drug effects* / Q000378:metabolism; D001921:Brain / Q000187:drug effects* / Q000378:metabolism; D002491:Central Nervous System Agents / Q000494:pharmacology; D055598:Chemical Phenomena; D015195:Drug Design; D006801:Humans; D008962:Models, Theoretical; D021281:Quantitative Structure-Activity Relationship
chemical_list: D002491:Central Nervous System Agents