Quinazoline-based multi-tyrosine kinase inhibitors: synthesis, modeling, antitumor and antiangiogenic properties.

In this work the synthesis and the biological evaluation of some novel anilinoquinazoline derivatives carrying modifications in the quinazoline scaffold and in the aniline moiety were reported. Preliminary cytotoxicity studies identified three derivatives, carrying dioxygenated rings fused on the quinazoline portion and the biphenylamino substituent as aniline portion, as the most effective compounds. Further investigations revealed that these compounds exhibited antiproliferative activity on a wide panel of human tumor cell lines through the inhibition of both receptor and nonreceptor TKs. Furthermore, the compound bearing the dioxolane nucleus was also able to inhibit in vivo tumor growth. Molecular modeling of these compounds into kinase domain suggested that the phenyl group allows favorable interaction energies with the target proteins: this feature is favored by fused dioxygenated ring at the 6,7 positions, whereas free rotating functions do not allow the correct placement of the molecule, thus impairing the inhibitory potency. Finally, the biphenylamino derivatives, at noncytotoxic concentrations, acted as antiangiogenic agents both in in vitro and in vivo assays.

New vandetanib analogs: fused tricyclic quinazolines with antiangiogenic potential.

The antiangiogenic effects of three novel anilinoquinazoline derivatives were studied with the aim to find new multi-kinase inhibitors as anticancer agents. The compounds are characterized by dioxolane, dioxane and dioxepine rings and bear the same aniline substituent in 4 position as vandetanib, known antiangiogenic agent. The in vitro assays were carried out on human umbilical vein endothelial cells (HUVECs), whereas in vivo angiogenesis was evaluated by means of Matrigel plug assay. The results showed that these compounds exert, even though to different extents, antiangiogenic activity affecting the various step of the process that leads to the formation of new blood vessels. At high concentrations they induced antiproliferative effects, whereas at non-cytotoxic concentrations they inhibited cell migration and the formation of tubular structures in Matrigel. In in vitro assays the dioxolane derivative 1 was more effective than vandetanib. Indeed, it inhibited the effects induced by exogenous VEGF and FGF-2 on both cell proliferation and morphogenesis, whereas vandetanib was completely ineffective. Moreover, all the compounds, as vandetanib, counteracted the FGF-2-induced increase in the hemoglobin content in the Matrigel plugs. Our results showed that all the three novel derivatives possess both in vitro and in vivo antiangiogenic activity, with compound 1 more effective than vandetanib to inhibit in vitro angiogenesis induced by exogenous cytokines.

Using the TOPS-MODE approach to fit multi-target QSAR models for tyrosine kinases inhibitors.

Tyrosine kinases constitute an eligible class of target for novel drug discovery. They resulted often overexpressed and/or deregulated in several cancer diseases. Thus, the development of novel tyrosine kinases inhibitors is of value, as well as the finding of novel cheminformatic tools for their design. Among the different ways to rationally design novel compounds, the Quantitative Structure-Activity Relationship (QSAR) plays a key role. The QSAR approach, in fact, allow the prediction of activity against a number of targets (multi-target QSAR), thus leading to models able to predict not only the activity of a compound, but also its selectivity versus a set of targets. Despite it is well known that tyrosine kinase inhibitors have to show multi-kinases inhibitory potency to be useful in anticancer therapy, only few multi-target computational tools have been developed to help medicinal chemists in the design of novel compounds. Herein we present the development of several multi-target classification QSAR (mtc-QSAR) models useful to assess the activity profile of the tyrosine kinases inhibitors.

The Importance of Descriptor-Based Clusterization in QSAR Models Development: Tyrosine Kinases Inhibitors as a Key Study.

Quantitative Structure Activity Relationship (QSAR) is a well known cheminformatic tool for the discovery of novel biologically active compounds. However, when large and heterogeneous datasets are mined, it is not possible to derive a QSAR equation able to predict in a satisfactory manner the activity of the compounds. Thus, QSAR models are often inadequate for virtual screening purpose. Herein we present a novel approach to multitarget classification QSAR models, useful to assess the selectivity profile of the tyrosine kinases inhibitors. A descriptor-based clusterization process was employed, that allowed the generation of models with high accuracies and independent from the chemical classification of the compounds (i.e. from the scaffold type). The herein proposed methodology can lead to QSAR models useful for virtual screening processes.

Exploring epidermal growth factor receptor (EGFR) inhibitor features: the role of fused dioxygenated rings on the quinazoline scaffold.

A number of dioxolane, dioxane, and dioxepine quinazoline derivatives have been synthetized and evaluated as EGFR inhibitors. Their cytotoxic activity has been tested against two cell lines overexpressing and not expressing EGFR. Most derivatives were able to counteract EGF-induced EGFR phosphorylation, and their potency was comparable to the reference compound PD153035. The size of the fused dioxygenated ring was crucial for the biological activity, the dioxane derivatives being the most promising class of this series.