Quantitative Drug Activity Prediction for Inhibitors of Human Breast Carcinoma

Abstract

There are sufficient data on a series of N−aryl−N-(2-chloroethyl) ureas tested as inhibitors of human breast carcinoma of the MDA-MB-231 cancer line to allow us to apply the so-called electron-conformational (EC) method in order to predict the drug activity of other molecular systems. The EC method reveals the pharmacophore and predicts the activity quantitatively based on conformational analysis and electronic structure calculations for a set of molecules that were tested for the activity under consideration (the training set). To reveal the pharmacophore of inhibitors of the human breast carcinoma MDA-MB-231 and to determine the parameters of molecular structure that enhance or diminish the activity, thus providing a tool for further increasing the inhibitor activity. Details of the EC method are described elsewhere. For the training set of the tested molecules, the electronic structure of the lowest conformations is calculated and presented in matrices, which are then processed in comparison with the activity. This reveals the pharmacophore: the special features of the drug molecules that are common for all active compounds and absent in the inactive ones. No arbitrary descriptors are used in the identification of the pharmacophore. The out-of-pharmacophore groups are then analysed and parameterised in an error-minimisation scheme that allows for calculation of the quantitative activity of any molecular system that has the pharmacophore. The pharmacophore of human breast carcinoma inhibitors is given by ten numbers with certain limits of flexibility. They represent four atoms (reactivity positions) with certain interatomic distances within the defined tolerances. Typical out-of-pharmacophore groups in the drug molecule serve as either antipharmacophore shields that diminish the activity or as other factors that may enhance the lipophilicity. A formula is obtained in which the roles of pharmacophore tolerances and out-of-pharmacophore group influences are presented by numerical coefficients, allowing the calculation of the expected activity quantitatively. The formula liability is estimated to be ≈97%. A cross-validation is performed showing that the prediction power is 92%. The pharmacophore evaluation is ≈100% correct, within the accuracy of the experimental data in the training set. An additional simple formula allows for the discrimination of the most active out-of-pharmacophore groups and the most influential pharmacophore tolerance parameters. The pharmacophore of the inhibitors of human breast carcinoma MDA-MB-231 is revealed and allows for high-accuracy data mining for potential drugs. A formula is derived for quantitative prediction of the activity of untested molecules with an expected accuracy of 92%.