Overview on the current status of virtual high-throughput screening and combinatorial chemistry approaches in multi-target anticancer drug discovery; Part I.

Conventional drug design embraces the "one gene, one drug, one disease" philosophy. Nowadays, new generation of anti- cancer drugs, able to inhibit more than one pathway, is believed to play a major role in contemporary anticancer drug research. In this way, polypharmacology, focusing on multi-target drugs, has emerged as a new paradigm in drug discovery. A number of recent successful drugs have in part or in whole emerged from a structure-based research approach. Many advances including crystallography and informatics are behind these successes. Increasing insight into the genetics and molecular biology of cancer has resulted in the identification of an increasing number of potential molecular targets, for anticancer drug discovery and development. These targets can be approached through exploitation of emerging structural biology, "rational" drug design, screening of chemical libraries, or a combination of these methods. The result is the rapid discovery of new anticancer drugs. In this article we discuss the application of molecular modeling, molecular docking and virtual high-throughput screening to multi-targeted anticancer drug discovery. Efforts have been made to employ in silico methods for facilitating the search and design of selective multi-target agents. These computer aided molecular design methods have shown promising potential in facilitating drug discovery directed at selective multiple targets and is expected to contribute to intelligent lead anticancer drugs.