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A recursive-partitioning model for blood–brain barrier permeation

A recursive-partitioning model for blood–brain barrier permeation A series of bagged recursive partitioning models for log(BB) is presented. Using a LGO-CV, three sets of physical property descriptors are evaluated and found to have Q2 values of 0.51 (CPSA), 0.53 (Ro5x) and 0.53 (MOE). Extrapolating these models to Pfizer chemical space is difficult due to P-glycoprotein (P-gp) mediated efflux. Low correlation coefficients for this test set are improved (R 2=0.39) when compounds known to be P-gp substrates or statistical extrapolations are removed. The use of simple linear models for specific chemical series is also found to improve the correlation over a limited chemical space. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Computer-Aided Molecular Design Springer Journals

A recursive-partitioning model for blood–brain barrier permeation

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References (100)

Publisher
Springer Journals
Copyright
Copyright © 2005 by Springer science + business media
Subject
Chemistry; Animal Anatomy / Morphology / Histology; Computer Applications in Chemistry ; Physical Chemistry
ISSN
0920-654X
eISSN
1573-4951
DOI
10.1007/s10822-005-9001-7
pmid
16331406
Publisher site
See Article on Publisher Site

Abstract

A series of bagged recursive partitioning models for log(BB) is presented. Using a LGO-CV, three sets of physical property descriptors are evaluated and found to have Q2 values of 0.51 (CPSA), 0.53 (Ro5x) and 0.53 (MOE). Extrapolating these models to Pfizer chemical space is difficult due to P-glycoprotein (P-gp) mediated efflux. Low correlation coefficients for this test set are improved (R 2=0.39) when compounds known to be P-gp substrates or statistical extrapolations are removed. The use of simple linear models for specific chemical series is also found to improve the correlation over a limited chemical space.

Journal

Journal of Computer-Aided Molecular DesignSpringer Journals

Published: Dec 6, 2005

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