Pharmacophore modelling as useful tool in the lead compounds identification and optimization

The goal of computer-aided molecular design methods in modern medicinal chemistry is to reduce the overall cost and time associated to the discovery and development of a new drug by identifying the most promising candidates to focus the experimental efforts on. Very often, many drug discovery projects have reached already a well-advanced stage before detailed structural data on the protein target have become available. A possible consequence is that often, medicinal chemists develop novel compounds for a target using preliminary structure–activity information, together with the theoretical models of interactions. Only responses that are consistent with the working hypothesis contribute to an evolution of the used models. Within this framework, the pharmacophore approach has proven to be successful, allowing the perception and understanding of key interactions between a receptor and a ligand[1]. In recent years, our research group exploited this useful modeling tool with the aim to identify new chemical entities and/or optimizing known lead compounds to obtain more active drugs in the field of antitumor, antiviral, and antibacterial drugs. In this communication, we present an overview of our recent works in which we used the pharmacophore modelling approach combined with induced fit docking, 3D-QSAR approach, and HTVS for the analysis of drug-receptor interactions and the discovery of new inhibitors of IKKβ, Bcl-xl, and c-kit tyrosine kinase, all targets involved into the initiation and the development of different types of cancer[2-5].