Current State and Future Perspectives in QSAR Models to Predict Blood Brain Barrier penetration in Central Nervous System Drug R&D

Autores
Morales, Juan Francisco; Scioli Montoto, Sebastián; Fagiolino, Pietro; Ruiz, María
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Facultad de Ciencias Exactas
Materia
Biología
Blood-brain barrier
Brain penetration
Central nervous system
Microdialysis
Passive difussion
Pharmacokinetic
QSAR models
Protein binding,
Unbound drug fraction
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/103692
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/103692
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Current State and Future Perspectives in QSAR Models to Predict Blood Brain Barrier penetration in Central Nervous System Drug R&DMorales, Juan FranciscoScioli Montoto, SebastiánFagiolino, PietroRuiz, MaríaBiologíaBlood-brain barrierBrain penetrationCentral nervous systemMicrodialysisPassive difussionPharmacokineticQSAR modelsProtein binding,Unbound drug fractionThe 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.Facultad de Ciencias Exactas2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/103692enginfo:eu-repo/semantics/altIdentifier/issn/1389-5575info:eu-repo/semantics/altIdentifier/doi/10.2174/1389557516666161013110813info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:54:44Zoai:sedici.unlp.edu.ar:10915/103692Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:54:45.137SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Current State and Future Perspectives in QSAR Models to Predict Blood Brain Barrier penetration in Central Nervous System Drug R&D
title Current State and Future Perspectives in QSAR Models to Predict Blood Brain Barrier penetration in Central Nervous System Drug R&D
spellingShingle Current State and Future Perspectives in QSAR Models to Predict Blood Brain Barrier penetration in Central Nervous System Drug R&D
Morales, Juan Francisco
Biología
Blood-brain barrier
Brain penetration
Central nervous system
Microdialysis
Passive difussion
Pharmacokinetic
QSAR models
Protein binding,
Unbound drug fraction
title_short Current State and Future Perspectives in QSAR Models to Predict Blood Brain Barrier penetration in Central Nervous System Drug R&D
title_full Current State and Future Perspectives in QSAR Models to Predict Blood Brain Barrier penetration in Central Nervous System Drug R&D
title_fullStr Current State and Future Perspectives in QSAR Models to Predict Blood Brain Barrier penetration in Central Nervous System Drug R&D
title_full_unstemmed Current State and Future Perspectives in QSAR Models to Predict Blood Brain Barrier penetration in Central Nervous System Drug R&D
title_sort Current State and Future Perspectives in QSAR Models to Predict Blood Brain Barrier penetration in Central Nervous System Drug R&D
dc.creator.none.fl_str_mv Morales, Juan Francisco
Scioli Montoto, Sebastián
Fagiolino, Pietro
Ruiz, María
author Morales, Juan Francisco
author_facet Morales, Juan Francisco
Scioli Montoto, Sebastián
Fagiolino, Pietro
Ruiz, María
author_role author
author2 Scioli Montoto, Sebastián
Fagiolino, Pietro
Ruiz, María
author2_role author
author
author
dc.subject.none.fl_str_mv Biología
Blood-brain barrier
Brain penetration
Central nervous system
Microdialysis
Passive difussion
Pharmacokinetic
QSAR models
Protein binding,
Unbound drug fraction
topic Biología
Blood-brain barrier
Brain penetration
Central nervous system
Microdialysis
Passive difussion
Pharmacokinetic
QSAR models
Protein binding,
Unbound drug fraction
dc.description.none.fl_txt_mv 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.
Facultad de Ciencias Exactas
description 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.
publishDate 2017
dc.date.none.fl_str_mv 2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/103692
url http://sedici.unlp.edu.ar/handle/10915/103692
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1389-5575
info:eu-repo/semantics/altIdentifier/doi/10.2174/1389557516666161013110813
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 13.13397

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