Project

Drug Discovery from Medicinal Plants using Machine Learning Approaches

Computational tools are widely used nowadays to aid research studies on early stage of drug development for known and new diseases. Big Data analytics with high performance computing machines and advances in molecular modeling software has revolutionized the in-silico drug discovery process. This study integrates PPI analysis with in-silico virtual screening in Drug discovery. For a selected disease of interest, potential drugs need to be discovered. We study the complete proteome of the disease using PPIs and select the Drug target molecules in the proteome. Virtual screening techniques will be used to identify potential drug likeliness compounds. Then we use computational docking studies to identify drug candidates for the selected disease. This study integrates PPI analysis with in-silico virtual screening in Drug discovery. For a selected disease of interest, potential drugs need to be discovered. We study the complete proteome of the disease using PPIs and select the Drug target molecules in the proteome. Virtual screening techniques will be used to identify potential drug likeliness compounds. Then we use computational docking studies to identify drug candidates for the selected disease.