Predicting Caco-2 cell permeation coefficients of organic molecules using membrane-interaction QSAR analysis

J Chem Inf Comput Sci. 2002 Mar-Apr;42(2):331-42. doi: 10.1021/ci010108d.

Abstract

A methodology termed membrane-interaction QSAR (MI-QSAR) analysis has been developed in order to predict the behavior of organic compounds interacting with the phospholipid-rich regions of biological membranes. One important application of MI-QSAR analysis is to estimate ADME properties including the transport of organic solutes through biological membranes as a computational approach to forecasting drug intestinal absorption. A training set of 30 structurally diverse drugs, whose permeability coefficients across the cellular membranes of Caco-2 cells were measured, was used to construct significant MI-QSAR models of Caco-2 cell permeation. Cellular permeation is found to depend primarily upon aqueous solvation free energy (solubility) of the drug, the extent of drug interaction with a model phospholipid (DMPC) monolayer, and the conformational flexibility of the solute within the model membrane. A test set of eight drugs was used to evaluate the predictivity of the MI-QSAR models. The permeation coefficients of the test set compounds were predicted with the same accuracy as the compounds of the training set.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Caco-2 Cells
  • Cell Membrane Permeability*
  • Humans
  • Membranes, Artificial
  • Models, Molecular
  • Organic Chemicals / metabolism*
  • Quantitative Structure-Activity Relationship

Substances

  • Membranes, Artificial
  • Organic Chemicals