<![CDATA[This study aims to systematically review and analyze in vitro approaches for evaluating bioactive natural compound–target interactions in early drug discovery, with myristicin highlighted as a representative example. Employing a qualitative descriptive research design, this study utilized a library-based method through the comprehensive analysis of scientific articles, books, and reports published between 2015 and 2025. Data collection involved literature screening and document analysis from peer-reviewed journals, while data analysis followed an inductive thematic approach encompassing identification, reduction, categorization, and synthesis of findings. The results indicate that integrating in vitro assays with computational (in silico) modeling significantly enhances predictive accuracy, efficiency, and mechanistic understanding in early drug discovery. Myristicin demonstrated multitarget bioactivity, including anti-inflammatory, antimicrobial, antioxidant, and anticancer effects, primarily through modulation of COX-2, PI3K/Akt/mTOR, and P-glycoprotein pathways. These findings reinforce the theoretical framework of polypharmacology, supporting the concept that natural compounds often act through multi-target interactions rather than single-receptor specificity. The study contributes to pharmacognosy and molecular pharmacology by providing a conceptual and methodological model for integrating experimental and computational drug discovery approaches. The implications extend to both academic and industrial domains, promoting standardized in vitro validation and translational research for natural product–based drug development.]]>
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