Advanced Drug Discovery Techniques for Identification of Natural Resources as Potential Therapeutic Agents

Emerging disease threat and the mortality rate associated with it has triggered the need for the identification of treatment and prevention of such diseases. Natural products are known for here therapeutic value and can act as a prominent source for the identification of new drugs for these diseases. Many different strategies have been developed to identify and obtain newer drugs from natural resources. Natural products are a potential source of drugs for many diseases due to their structural diversity and already reported biological activity. Lead compounds for many lethal diseases, such as the recently emerged infectious disease COVID-19 have been identified using computational techniques which may help to curb the COVID-19 outbreak. Omics-based techniques such as proteomics, genomics, metabolomics, transcriptomics, etc, have become one of the most helpful techniques for discovering drug products from natural resources. CRISPR is another such technique that combines bioinformatics, genomics and synthetic biology. It is a DNA-targeting genome editing tool that has aided medical research. Other than these, many more drug discovery tools such as multi-omics, combinatorial biosynthesis, artificial intelligence and 3D printing have been a boon for identifying natural products with diverse chemical structures and therapeutic indexes. Advanced computational techniques have helped develop potential drug candidates with desired therapeutic activity. This chapter focuses on recent computational techniques employed to discover drugs from natural resources. 

Keywords: Artificial intelligence, Combinatorial biosynthesis, Computational technique, CRISPR, Multi-omics, 3D-Printing.