MEDICINAL PLANTS AND PHYTOCHEMICAL DIVERSITY: CHARACTERIZATION OF BIOACTIVE COMPOUNDS AND THEIR BIOLOGICAL ACTIVITIES

Abstract

Plant secondary metabolites represent an evolutionary adaptation enabling flora to withstand abiotic stress, defend against pathogens, and mediate ecological interactions. These specialized compounds including polyphenols, flavonoids, alkaloids, terpenoids, saponins, steroids, and glycosides exhibit extraordinary structural diversity with significant pharmacological potential. This review critically evaluates the ecological and biogeographical drivers of phytochemical variation, contrasts conventional extraction protocols with Natural Deep Eutectic Solvent (NADES)-based green extraction technologies, outlines advanced spectroscopic characterization methodologies, and details pharmacological mechanisms underlying antibacterial, antioxidant, cytotoxic, and anti-inflammatory activities. Phytochemical composition is dynamically regulated by genetic factors and environmental conditions, with abiotic stress such as UV radiation, water deficits, and temperature fluctuations upregulating specific secondary metabolic pathways. Geographic origin and tissue-specific gene expression further influence metabolite accumulation, as demonstrated in Prosopis farcta, Azadirachta indica, and Reynoutria species. Conventional extraction methods including Soxhlet and maceration suffer from thermal degradation, toxic solvent consumption, and low selectivity. NADES combined with Ultrasound-Assisted Extraction offers sustainable alternatives, achieving 2- to 6-fold higher bioactive recovery at mild temperatures (≤40°C) while protecting labile compounds. Advanced analytical platforms UPLC-HRMS, NMR spectroscopy, and Feature-Based Molecular Networking through GNPS have accelerated dereplication and novel compound identification. Pharmacological evaluations demonstrate that phenolics, terpenoids, and alkaloids disrupt bacterial membranes (MIC 0.06–0.50 mg/mL), neutralize reactive oxygen species via Hydrogen Atom Transfer and Single Electron Transfer mechanisms, induce apoptosis in cancer cell lines, suppress NF-κB-mediated inflammation, and inhibit α-glucosidase and α-amylase for diabetes management. However, methodological heterogeneity, standardization bottlenecks, NADES industrial scale-up challenges, and spectral database limitations constrain clinical translation. Integrating machine learning algorithms and expanded spectral libraries promises to bridge unannotated "dark matter" gaps in phytochemical discovery.