In Silico Prediction of Membrane Permeability from Calculated Molecular Parameters.

Hanne H.F. Refsgaard, Berith F. Jensen, Per B. Brockhoff, Søren B. Padkjær, Mette Guldbrandt, Michael S. Christensen

Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

Abstract

A data set consisting of 712 compounds was used for classification into two classes with respect to membrane permeation in a cell-based assay:  (0) apparent permeability (Papp) below 4 × 10(-6) cm/s and (1) (Papp) on 4 × 10(-6) cm/s or higher. Nine molecular descriptors were calculated for each compound and Nearest-Neighbor classification was applied using five neighbors as optimized by full cross-validation. A model based on five descriptors, number of flex bonds, number of hydrogen bond acceptors and donors, and molecular and polar surface area, was selected by variable selection. In an external test set of 112 compounds, 104 compounds were classified and 8 compounds were judged as “unknown”. Among the 104 compounds, 16 were misclassified corresponding to a misclassification rate of 15% and no compounds were falsely predicted in the nonpermeable class.
Original languageEnglish
JournalJournal of Medicinal Chemistry
Volume48
Issue number3
Pages (from-to)805-811
ISSN0022-2623
Publication statusPublished - 2005
Externally publishedYes

Keywords

  • Membrane permeation
  • Cell-based assay
  • Apparent permeability (Papp)
  • Molecular descriptors
  • Nearest-Neighbor classification

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