Natural products remain a vital source of drug discovery due to their vast structural diversity and broad spectrum of biological activities. This review highlights the significance of medicinal plants and phytochemicals as therapeutic agents and examines the integration of computational techniques in modern natural product–based drug development. Major classes of bioactive compounds, including alkaloids, flavonoids, terpenoids, phenolics, and glycosides, exhibit diverse pharmacological effects such as antioxidant, antimicrobial, anticancer, neuroprotective, and anti-inflammatory activities. Advances in computer-aided drug design (CADD), including molecular docking, virtual screening, molecular dynamics simulations, and quantitative structure–activity relationship (QSAR) modeling, have significantly accelerated the identification and optimization of potential drug candidates. Furthermore, network pharmacology provides a systems-level understanding of drug–target–disease interactions by integrating omics data and computational modeling. Applications in cancer, neurodegenerative diseases, inflammation, and metabolic disorders demonstrate the therapeutic potential of natural products. Despite challenges such as data quality and standardization, integrating natural product research with artificial intelligence and multi-omics technologies offers promising prospects for future drug discovery.
Adamu Benjamin (Tue,) studied this question.