Predicting permeability of antimycotics from calculated chemodescriptors: A hierarchical QSAR approach

Subhash C Basak, Denise Mills

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Quantitative structure-activity relationship (QSAR) models were developed for the prediction of bovine hoof membrane permeability in an effort to gain insight into the rate of penetration of antimycotics through the nail plate. Numerical descriptors based on chemical structure were calculated for a set of 14 drugs, mainly antimycotics. The descriptors were then placed into one of three classes based on level of complexity and demand for computational resources. Models using the various classes of structural descriptors were developed using ridge regression, principal component regression, and partial least squares. Results indicate that permeability of antimycotics can be modeled based on structural descriptors alone, without the need for experimental data. As such, predictions can be made about the permeability of hypothetical compounds of similar structure not yet synthesized. However, additional data are required to allow for reliable modeling of human nail plate permeability.

Original languageEnglish (US)
Pages (from-to)954-957
Number of pages4
JournalWSEAS Transactions on Information Science and Applications
Volume2
Issue number7
StatePublished - Jul 1 2005

Keywords

  • Antimycotics
  • Chemodescriptors
  • Hierarchical quantitative structure-activity relationship
  • Hoof membrane
  • Nail plate
  • Permeability

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