Literature DB >> 18481317

Ionization-specific prediction of blood-brain permeability.

Kiril Lanevskij1, Pranas Japertas, Remigijus Didziapetris, Alanas Petrauskas.   

Abstract

This study presents a mechanistic QSAR analysis of passive blood-brain barrier permeability of drugs and drug-like compounds in rats and mice. The experimental data represented in vivo log PS (permeability-surface area product) from in situ perfusion, brain uptake index, and intravenous administration studies. A data set of 280 log PS values was compiled. A subset of 178 compounds was assumed to be driven by passive transport that is free of plasma protein binding and carrier-mediated effects. This subset was described in terms of nonlinear lipophilicity and ionization dependences, that account for multiple kinetic and thermodynamic effects: (i) drug's kinetic diffusion, (ii) ion-specific partitioning between plasma and brain capillary endothelial cell membranes, and (iii) hydrophobic entrapment in phospholipid bilayer. The obtained QSAR model provides both good statistical significance (RMSE < 0.5) and simple physicochemical interpretations (log P and pKa), thus providing a clear route towards property-based design of new CNS drugs. (c) 2008 Wiley-Liss, Inc. and the American Pharmacists Association

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Year:  2009        PMID: 18481317     DOI: 10.1002/jps.21405

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  14 in total

Review 1.  Methodologies to assess drug permeation through the blood-brain barrier for pharmaceutical research.

Authors:  Céline Passeleu-Le Bourdonnec; Pierre-Alain Carrupt; Jean Michel Scherrmann; Sophie Martel
Journal:  Pharm Res       Date:  2013-06-26       Impact factor: 4.200

2.  Biorelevant pK(a) (37 °C) predicted from the 2D structure of the molecule and its pK(a) at 25 °C.

Authors:  Na Sun; Alex Avdeef
Journal:  J Pharm Biomed Anal       Date:  2011-05-17       Impact factor: 3.935

3.  Correlation between molecular acidity (pKa) and vibrational spectroscopy.

Authors:  Niraj Verma; Yunwen Tao; Bruna Luana Marcial; Elfi Kraka
Journal:  J Mol Model       Date:  2019-01-30       Impact factor: 1.810

Review 4.  Challenges of using in vitro data for modeling P-glycoprotein efflux in the blood-brain barrier.

Authors:  Noora Sjöstedt; Hanna Kortejärvi; Heidi Kidron; Kati-Sisko Vellonen; Arto Urtti; Marjo Yliperttula
Journal:  Pharm Res       Date:  2014-01       Impact factor: 4.200

5.  Improved Prediction of Blood-Brain Barrier Permeability Through Machine Learning with Combined Use of Molecular Property-Based Descriptors and Fingerprints.

Authors:  Yaxia Yuan; Fang Zheng; Chang-Guo Zhan
Journal:  AAPS J       Date:  2018-03-21       Impact factor: 4.009

6.  Role of breast cancer resistance protein (BCRP) as active efflux transporter on blood-brain barrier (BBB) permeability.

Authors:  Prabha Garg; Rahul Dhakne; Vilas Belekar
Journal:  Mol Divers       Date:  2014-12-14       Impact factor: 2.943

7.  Physicochemical selectivity of the BBB microenvironment governing passive diffusion--matching with a porcine brain lipid extract artificial membrane permeability model.

Authors:  Oksana Tsinman; Konstantin Tsinman; Na Sun; Alex Avdeef
Journal:  Pharm Res       Date:  2010-10-14       Impact factor: 4.200

8.  P-glycoprotein deficient mouse in situ blood-brain barrier permeability and its prediction using an in combo PAMPA model.

Authors:  Claude Dagenais; Alex Avdeef; Oksana Tsinman; Adam Dudley; Richard Beliveau
Journal:  Eur J Pharm Sci       Date:  2009-07-08       Impact factor: 4.384

Review 9.  Prediction of drug disposition on the basis of its chemical structure.

Authors:  David Stepensky
Journal:  Clin Pharmacokinet       Date:  2013-06       Impact factor: 6.447

10.  Identification of novel functional inhibitors of acid sphingomyelinase.

Authors:  Johannes Kornhuber; Markus Muehlbacher; Stefan Trapp; Stefanie Pechmann; Astrid Friedl; Martin Reichel; Christiane Mühle; Lothar Terfloth; Teja W Groemer; Gudrun M Spitzer; Klaus R Liedl; Erich Gulbins; Philipp Tripal
Journal:  PLoS One       Date:  2011-08-31       Impact factor: 3.240

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