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

Acta Pharmacologica Sinica
Li-li ChenJie Yang


To use membrane-interaction quantitative structure-activity relationship analysis (MI-QSAR) to develop predictive models of partitioning of organic compounds in gastrointestinal cells. A training set of 22 structurally diverse compounds, whose apparent permeability across cellular membranes of Madin-Darby canine kidney (MDCK) cells were measured, were used to construct MI-QSAR models. Molecular dynamic simulations were used to determine the explicit interaction of each test compound (solute) with a dimyristoyl-phosphatidyl-choline monolayer membrane model. An additional set of intramolecular solute descriptors were computed and considered in the trial pool of descriptors for building MI-QSAR models. The QSAR models were optimized using multidimensional linear regression fitting and the stepwise method. A test set of 8 compounds were evaluated using the MI-QSAR models as part of a validation process. MI-QSAR models of the gastrointestinal absorption process were constructed. The descriptors found in the best MI-QSAR models are as follows: 1) ClogP (the logarithm of the 1-octanol/water partition coefficient); 2) E(HOMO) (the highest occupied molecular orbital energy); 3) E(s) (stretch energy); 4) PM(Y) (the principal moment of in...Continue Reading


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