Prediction of polar surface area and drug transport processes using simpleparameters and PLS statistics

Modeling of the calculated polar surface area of drugs with rapidly derived descriptors (i.e., the number of hydrogen bonds accepting oxygen and nitro gen atoms and the number of hydrogen atoms bonded to these) using partial l east squares projection to latent structures (PLS) analysis is described. T he statistical analysis showed strong relationships between the hydrogen-bo nding;descriptors and the calculated polar surface area of five chemically diverse-sets of drugs (R-2 > 0.93 and Q(2) > 0.69, n = 11, 20, 45, 70, and 74, respectively). The statistical models (using H-bonding descriptors and log P) of transport across Caco-2 cells (n ii), brain-blood partitioning (t wo data sets, pz = 45 and 70) and percent intestinal absorption (n 20) show ed R-2 = 0.92, 0.72, 0.76, and 0.81 and Q(2) = 0.74, 0.75, 0.71, and 0.73, respectively. The inclusion of log P improved two models, had no effect on one model, and had a slightly negative impact on one model The combination of H-bonding,descriptors with log P is similar to the Lipinski "rule-of-fiv e" mnemonic. However, by using a multivariate statistical method (e.g., PLS ), the prediction becomes quantitative instead of qualitative. Good statist ical models were derived which. permit fast computational screening and pri oritization of virtual compound libraries.