ABSTRACT
The development of novel, efficient, and affordable antineoplastic medications is necessary given the growing incidence of cancer in the world. Active phytochemicals and secondary metabolites found in plants, such as flavonoids, carotenoids, alkaloids, phenolics, etc., are being researched in terms of cancer healing processes and have demonstrated pleiotropic positive impact both in vitro and in vivo. Conventional screening protocols for lead molecules involving the use of experimental animals and in vitro drug screening have achieved remarkable success, but they are typically time-consuming, expensive, and labour intensive, thus emphasizing the demand for effective methods such as bioinformatics tools, which can enhance the current drug discovery process.
Bioinformatics approaches provide a great opportunity for identifying potential compounds, and their application in cancer research has grown dramatically during the last decade. Omics data explosion offers development of cutting-edge cancer drug research by enabling computer-based prediction of antiproliferative drugs, where it is advantageous in calculating all the possible combinations iteratively and in identifying an efficient multi-component therapy. Systems pharmacology and cheminformatics are most essentially employed in the identification of novel therapeutic chemicals from medicinal plants. QSAR and ADMET support evaluation of bioactivities and pharmacokinetic properties of the lead molecules. In addition, the complex genomic makeup of each individual tumour could be analysed using artificial intelligence techniques to produce accurate predictions of therapeutic response(s). This chapter merges the sphere of computer-based methods in ‘omics’ technologies with the analysis of plant-based antineoplastic agents and discusses the sophisticated bioinformatics software and tools adopted in the process. It is strongly believed that the general overview of available databases and current computational methods and the clinical information of cancer patients will accelerate the process of drug selection and help in the development of cost-effective and accurate cancer therapeutics.
