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]
