title: Predicting Caco-2 cell permeation coefficients of organic molecules using membrane-interaction QSAR analysis.
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.
authors.affiliation: Laboratory of Molecular Modeling and Design (M/C 781), College of Pharmacy, The University of Illinois at Chicago, 833 South Wood Street, Chicago, Illinois 60612-7231, USA.
authors.forename: Amit
authors.initials: A
authors.lastname: Kulkarni
authors.forename: Yi
authors.initials: Y
authors.lastname: Han
authors.forename: A J
authors.initials: AJ
authors.lastname: Hopfinger
mesh_terms: D018938:Caco-2 Cells; D002463:Cell Membrane Permeability; D006801:Humans; D008567:Membranes, Artificial; D008958:Models, Molecular; D009930:Organic Chemicals / Q000378:metabolism*; D021281:Quantitative Structure-Activity Relationship
chemical_list: D008567:Membranes, Artificial; D009930:Organic Chemicals