Currently, cancer has become one of the most dreadful diseases threatening
human health. Natural plant sources play a vital role in the development of several
anti-cancer drugs such as vincristine, vinblastine, vinorelbine, docetaxel, paclitaxel,
camptothecin, etoposide, teniposide, etc. Various chemotherapies fail due to adverse
reactions, target specificity, and drug resistance of some types of drugs. Researchers
are attentive to developing drugs that overcome the problems stated above by using
natural compounds that may affect multiple targets with reduced adverse effects and
that are effective against several cancer types. The development of a new drug is a
highly complex, expensive, and time-consuming endeavour. In the traditional drug
discovery process, ending with a new medicine ready for the market can take up to 15
years and cost more than one billion dollars. Fortunately, this situation has changed
with the arrival of novel approaches recently. Many new technologies and
methodologies have been developed to increase the efficiency of the drug discovery
process, and computational methodologies utilise the existing data to generate
knowledge that affords valuable understanding for addressing current complications
and guiding the further research and development of new naturally derived drugs.
Consequently, the application of in silico techniques and optimization algorithms in
drug discovery ventures can provide versatile solutions to understand the molecular-level interactions of chemical constituents and identify the hits. Lead optimization
techniques such as ligand-based or structure-based drug design are widely used in
many discovery efforts. In this chapter, we first introduce the concepts of CADD, in
silico tools, etc. we then describe how this virtual screening has been successfully
applied. Furthermore, we review the concept of natural product anticancer therapies and present some of the most representative examples of molecules identified through
this method.
Keywords: Anticancer, ADME Tool, Bioinformatics, Cancer, CADD, Drug discovery, Drug likeness, In silico tools, Ligand, Lead optimization. Phytochemical properties, Molecular docking, Natural anticancer molecule, Molecular dynamics, Pass Tool, Targets, Virtual screening.
