NDLI: Qualitative prediction of blood–brain barrier permeability on a large and refined dataset

Content Provider	Springer Nature Link
Author	Muehlbacher, Markus Spitzer, Gudrun M. Liedl, Klaus R. Kornhuber, Johannes
Copyright Year	2011
Abstract	The prediction of blood–brain barrier permeation is vitally important for the optimization of drugs targeting the central nervous system as well as for avoiding side effects of peripheral drugs. Following a previously proposed model on blood–brain barrier penetration, we calculated the cross-sectional area perpendicular to the amphiphilic axis. We obtained a high correlation between calculated and experimental cross-sectional area (r = 0.898, n = 32). Based on these results, we examined a correlation of the calculated cross-sectional area with blood–brain barrier penetration given by logBB values. We combined various literature data sets to form a large-scale logBB dataset with 362 experimental logBB values. Quantitative models were calculated using bootstrap validated multiple linear regression. Qualitative models were built by a bootstrapped random forest algorithm. Both methods found similar descriptors such as polar surface area, pKa, logP, charges and number of positive ionisable groups to be predictive for logBB. In contrast to our initial assumption, we were not able to obtain models with the cross-sectional area chosen as relevant parameter for both approaches. Comparing those two different techniques, qualitative random forest models are better suited for blood-brain barrier permeability prediction, especially when reducing the number of descriptors and using a large dataset. A random forest prediction system (n$_{trees}$ = 5) based on only four descriptors yields a validated accuracy of 88%.
Starting Page	1095
Ending Page	1106
Page Count	12
File Format	PDF
ISSN	0920654X
Journal	Journal of Computer-Aided Molecular Design
Volume Number	25
Issue Number	12
e-ISSN	15734951
Language	English
Publisher	Springer Netherlands
Publisher Date	2011-11-23
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Blood–brain barrier Central nervous system Membrane permeability QSAR LogBB Random forest Physical Chemistry Animal Anatomy / Morphology / Histology Computer Applications in Chemistry
Content Type	Text
Resource Type	Article
Subject	Drug Discovery Physical and Theoretical Chemistry Computer Science Applications

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