Recent trends and applications in 3D virtual screening.

Virtual screening (VS) is becoming an increasingly important approach for identifying and selecting biologically active molecules against specific pharmaceutically relevant targets. Compared to conventional high throughput screening techniques, in silico screening is fast and inexpensive, and is increasing in popularity in early-stage drug discovery endeavours. This paper reviews and discusses recent trends and developments in three-dimensional (3D) receptor-based and ligand-based VS methodologies. First, we describe the concept of accessible chemical space and its exploration. We then describe 3D structural ligand-based VS techniques, hybrid approaches, and new approaches to exploit additional knowledge that can now be found in large chemogenomic databases. We also briefly discuss some potential issues relating to pharmacokinetics, toxicity profiling, target identification and validation, inverse docking, scaffold-hopping and drug re-purposing. We propose that the best way to advance the state of the art in 3D VS is to integrate complementary strategies in a single drug discovery pipeline, rather than to focus only on theoretical or computational improvements of individual techniques. Two recent 3D VS case studies concerning the LXR-ß receptor and the CCR5/CXCR4 HIV co-receptors are presented as examples which implement some of the complementary methods and strategies that are reviewed here.

Exploring c-Met kinase flexibility by sampling and clustering its conformational space.

It is now widely recognized that the flexibility of both partners has to be considered in molecular docking studies. However, the question how to handle the best the huge computational complexity of exploring the protein binding site landscape is still a matter of debate. Here we investigate the flexibility of c-Met kinase as a test case for comparing several simulation methods. The c-Met kinase catalytic site is an interesting target for anticancer drug design. In particular, it harbors an unusual plasticity compared with other kinases ATP binding sites. Exploiting this feature may eventually lead to the discovery of new anticancer agents with exquisite specificity. We present in this article an extensive investigation of c-Met kinase conformational space using large-scale computational simulations in order to extend the knowledge already gathered from available X-ray structures. In the process, we compare the relevance of different strategies for modeling and injecting receptor flexibility information into early stage in silico structure-based drug discovery pipeline. The results presented here are currently being exploited in on-going virtual screening investigations on c-Met.

Identification of new aminoacid amides containing the imidazo[2,1-b]benzothiazol-2-ylphenyl moiety as inhibitors of tumorigenesis by oncogenic Met signaling.

The Met receptor tyrosine kinase is a promising target in anticancer therapies for its role during tumor evolution and resistance to treatment. It is characterized by an unusual structural plasticity as its active site accepts different inhibitor binding modes. Such feature can be exploited to identify distinct agents targeting tumor dependence and/or resistance by oncogenic Met. Here we report the identification of bioactive agents, featuring a new 4-(imidazo[2,1-b]benzothiazol-2-yl)phenyl moiety, targeting cancer cells dependent on oncogenic Met. One of these compounds (7c; Triflorcas) impairs survival, anchorage-independent growth, and in vivo tumorigenesis, without showing side effects. Our medicinal chemistry strategy was based on an in-house Met-focused library of aminoacid-amide derivatives enriched through structure-based computer modeling, taking into account the Met multiple-binding-mode feature. Altogether, our findings show how a rational structure-based drug design approach coupled to cell-based drug evaluation strategies can be applied in medicinal chemistry to identify new agents targeting a given oncogenic-dependency setting.

Analysis of c-Met kinase domain complexes: a new specific catalytic site receptor model for defining binding modes of ATP-competitive ligands.

The receptor tyrosine kinase c-Met have multiple roles during cancer development and is currently considered as an important target for molecularly targeted therapies. Structural knowledge of how compounds interact on c-Met catalytic site could guide structure-based drug design strategies towards more effective and selective anticancer drug candidates. However, although 17 crystal structures of c-Met complexed with adenosine triphosphate (ATP)-competitive kinase inhibitors are publicly available (August 2009), there are still open questions regarding the prediction of ligand binding modes. We have applied molecular modeling and molecular mechanics to analyze the distribution of ligands interaction energy on c-Met residues, and deduced a new model of the active site allowing for an unambiguous identification of ligand binding modes. We demonstrate that the binding of known ligands on the c-Met catalytic site involves seven identified structurally-distinct areas. Five of these match the generic kinase ATP binding site model built by Novartis scientists in the 1990s, while the two others are distinct allosteric regions that can be exploited by second generation kinase inhibitors such as Gleevec. We show here that c-Met can accept both such kinds of allosteric inhibitors, a very unusual feature in the kinase family that opens new grounds for highly specific drug design.