Simulation of Drug-Phytochemical Interactions Using Artificial Intelligence (AI)

The prevalence for a number of diseases has developed a scenario where conventional treatment methods fail to achieve complete remedies. Researchers are exploring computer-aided drug design for therapeutic development, as developed exponentially during COVID-19. Artificial intelligence (AI) has opened new avenues for screening phytochemicals from medicinal plants based on their physicochemical properties to predict their absorption, distribution, metabolism, excretion, and toxicity (ADMET). These advancements have reduced the cost and time required to evaluate the specific targets of phytochemicals through molecular docking (MD) analysis. Computer-aided drug design has revolutionized the drug discovery process, achieving a high level of accuracy. This chapter introduces the role of AI in evaluating phytochemicals for target prediction through molecular docking, as well as the role of other computational tools involved.