skip to main content
Show Results with:

Predictivity Approach for Quantitative Structure-Property Models. Application for Blood-Brain Barrier Permeation of Diverse Drug-Like Compounds

International Journal of Molecular Sciences, 2011, Vol.12(7), pp.4348-4364 [Peer Reviewed Journal]

Full text available

  • Title:
    Predictivity Approach for Quantitative Structure-Property Models. Application for Blood-Brain Barrier Permeation of Diverse Drug-Like Compounds
  • Author: Bolboaca, Sorana ; Jäntschi, Lorentz
  • Found In: International Journal of Molecular Sciences, 2011, Vol.12(7), pp.4348-4364 [Peer Reviewed Journal]
  • Subjects: in Silico Prediction ; Partition-Coefficient ; Blood-Brain Barrier (BBB) ; Permeation ; Structure-Property Relationship (SPR) ; Molecular Descriptors Family on Vertices Cutting (Mdfv)
  • Language: English
  • Description: The goal of the present research was to present a predictivity statistical approach applied on structure-based prediction models. The approach was applied to the domain of blood-brain barrier (BBB) permeation of diverse drug-like compounds. For this purpose, 15 statistical parameters and associated 95% confidence intervals computed on a 2 × 2 contingency table were defined as measures of predictivity for binary quantitative structure-property models. The predictivity approach was applied on a set of compounds comprised of 437 diverse molecules, 122 with measured BBB permeability and 315 classified as active or inactive. A training set of 81 compounds (~2/3 of 122 compounds assigned randomly) was used to identify the model and a test set of 41 compounds was used as the internal validation set. The molecular descriptor family on vertices cutting was the computation tool used to generate and calculate structural descriptors for all compounds. The identified model was assessed using the predictivity...
  • Identifier: ISSN: 16616596 ; E-ISSN: 14220067 ; DOI: 10.3390/ijms12074348

Searching Remote Databases, Please Wait