Although the Abelson (Abl) tyrosine kinase inhibitor imatinib mesylate has improved the treatment of breakpoint cluster region-Abl (Bcr-Abl)-positive leukemia, resistance is often reported in patients with advanced-stage disease. Although several Src inhibitors are more effective than imatinib and simultaneously inhibit Lyn, whose overexpression is associated with imatinib resistance, these inhibitors are less specific than imatinib.We have identified a specific dual Abl-Lyn inhibitor, NS-187 (elsewhere described as CNS-9), which is 25 to 55 times more potent than imatinib in vitro. NS-187 is also at least 10 times as effective as
The objective of this study was to develop rapid and reliable methods to predict the percent human intestinal absorption (%HIA) of compounds based on their 2D descriptors. The analyzed data set included 86 drug and drug-like molecules and was the same as that studied by Wessel and co-workers. Instead of using three-dimensional descriptors such as polar surface area, which require lengthy computations, we employed only two-dimensional topological descriptors derived from information about the two-dimensional structure of molecules. The %HIA values were modeled using a general regression neural network (GRNN) and a probabilistic neural network (PNN), variants of normalized radial basis function networks. Both networks performed well to model the %HIA values. The root-mean square (rms) error was 22.8 %HIA unit for the external prediction set for a GRNN model, and 80% of the external prediction set was correctly classified for a PNN model, indicating the potential of our approach to estimate the %HIA values for a large set of compounds as virtual libraries.
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