<p>Traditional drug discovery, largely based on the “one drug–one target” paradigm, has demonstrated limited effectiveness in addressing complex, multifactorial diseases such as cancer, metabolic syndrome, and neurodegenerative disorders. These conditions involve highly interconnected molecular networks that are insufficiently targeted by single-agent therapies. Network pharmacognosy has emerged as a promising paradigm shift, emphasizing scaffold diversity and phytochemical synergy for multi-target drug design. A comprehensive review of recent literature from databases such as PubMed, Scopus, and clinical trial registries highlights the integration of systems biology, omics technologies, and computational network–based tools in evaluating scaffold-driven multi-target interactions. Natural product scaffolds, including flavonoids, alkaloids, terpenoids, and polyphenols, exhibit significant multi-target pharmacological potential. Key phytochemicals such as curcumin, berberine, resveratrol, and green tea catechins regulate critical biological pathways associated with oxidative stress, inflammation, metabolic imbalance, and apoptosis. Evidence from preclinical and clinical studies suggests that synergistic combinations, such as berberine with silymarin and curcumin with resveratrol, enhance therapeutic efficacy while reducing toxicity compared to monotherapies. Overall, network pharmacognosy offers a transformative framework that bridges traditional medicinal knowledge with modern systems pharmacology. By elucidating mechanisms of phytochemical synergy and multi-target interactions, it provides a rational foundation for developing next-generation phytopharmaceuticals. The integration of multi-omics approaches, artificial intelligence, and rigorous clinical validation will be crucial for translating these insights into safe and effective therapies for complex human diseases.</p> Graphical Abstract <p></p>