A pharmacophore model, Hypo1, was built on the basis of 21 training-set indole compounds with varying levels of antiproliferative activity. Hypo1 possessed important chemical features required for the inhibitors and demonstrated good predictive ability for biological activity, with high correlation coefficients of 0.96 and 0.89 for the training-set and test-set compounds, respectively. Further utilization of the Hypo1 pharmacophore model to screen chemical database in silico led to the identification of four compounds with antiproliferative activity. Among these four compounds, 43 showed potent antiproliferative activity against various cancer cell lines with the strongest inhibition on the proliferation of KB cells (IC(50) = 187 nM). Further biological characterization revealed that 43 effectively inhibited tubulin polymerization and significantly induced cell cycle arrest in G(2)-M phase. In addition, 43 also showed the in vivo-like anticancer effects. To our knowledge, 43 is the most potent antiproliferative compound with antitubulin activity discovered by computer-aided drug design. The chemical novelty of 43 and its anticancer activities make this compound worthy of further lead optimization.

A series of aroylnaphthalene derivatives were prepared as bioisosteres of combrestatin A-4 and evaluated for anticancer activity. 2-Amino-1-aroylnaphthalene and 2-hydroxy-1-aroylnaphthalene, 9 and 8, respectively, showed strong antiproliferative activity with IC(50) values of 2.1-26.3 nM against a panel of human cancer cell lines including multiple-drug resistant cell line. Compound 9 demonstrated better antiproliferative activity and has a comparable tubulin binding efficacy as that of colchicine.

No abstract