A porphodimethene chemical inhibitor of uroporphyrinogen decarboxylase.

Uroporphyrinogen decarboxylase (UROD) catalyzes the conversion of uroporphyrinogen to coproporphyrinogen during heme biosynthesis. This enzyme was recently identified as a potential anticancer target; its inhibition leads to an increase in reactive oxygen species, likely mediated by the Fenton reaction, thereby decreasing cancer cell viability and working in cooperation with radiation and/or cisplatin. Because there is no known chemical UROD inhibitor suitable for use in translational studies, we aimed to design, synthesize, and characterize such a compound. Initial in silico-based design and docking analyses identified a potential porphyrin analogue that was subsequently synthesized. This species, a porphodimethene (named PI-16), was found to inhibit UROD in an enzymatic assay (IC50 = 9.9 µM), but did not affect porphobilinogen deaminase (at 62.5 µM), thereby exhibiting specificity. In cellular assays, PI-16 reduced the viability of FaDu and ME-180 cancer cells with half maximal effective concentrations of 22.7 µM and 26.9 µM, respectively, and only minimally affected normal oral epithelial (NOE) cells. PI-16 also combined effectively with radiation and cisplatin, with potent synergy being observed in the case of cisplatin in FaDu cells (Chou-Talalay combination index <1). This work presents the first known synthetic UROD inhibitor, and sets the foundation for the design, synthesis, and characterization of higher affinity and more effective UROD inhibitors.

Synthesis and evaluation of 3-aroylindoles as anticancer agents: metabolite approach.

BPR0L075 (2) is a potential anticancer drug candidate designed from Combretastatin A-4 (1) based on the bioisosterism principle. Metabolites of 2, proposed from in vitro human microsome studies, were synthesized, leading to the identification of metabolite-derived analogue 10 with 40-350 pM potency against various cancer cell lines. Insights gained from the major inactive metabolite of 2 led to the development of 29, with better pharmacokinetics and improved potency in the tumor xenograft model than 2.

Generation of ligand-based pharmacophore model and virtual screening for identification of novel tubulin inhibitors with potent anticancer activity.

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.

Synthesis and structure-activity relationships of 2-amino-1-aroylnaphthalene and 2-hydroxy-1-aroylnaphthalenes as potent antitubulin agents.

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.

A three-dimensional pharmacophore model for dipeptidyl peptidase IV inhibitors.

Dipeptidyl peptidase IV (DPP-IV) is a valid drug target for type-2 diabetes and DPP-IV inhibitors have been proven to efficiently improve glucose tolerance. In our study, 3D pharmacophore models were generated using a training set of 22 DPP-IV inhibitors. The best model consisted of important chemical features and mapped well into the active site of DPP-IV. The model gave high correlation coefficients of 0.97 and 0.84 for the training set and the test set, respectively, showing its good predictive ability for biological activity. Furthermore, the pharmacophore model demonstrated the capability to retrieve inhibitors from database with a high enrichment factor of 42.58. All results suggest that the model provides a useful tool for designing novel DPP-IV inhibitors.