Leveraging Biochemometrics to Prioritize Biologically Relevant Compounds from Natural Product Mixtures: A Journey from Conception to Successful Outcomes

Biochemometrics has evolved as a powerful tool in natural product research that enables the simultaneous identification of reliable putative bioactive compounds, while offering insights into the chemical composition of complex natural product extracts. The approach has steadily evolved from its initial phase with the advent of sophisticated and highly sensitive MS- and NMR-based analytical techniques, and has greatly impacted natural product drug discovery pipelines by complementing bioassay-guided fractionation. It has proven effective in identifying active compounds within natural product mixtures and investigating synergistic effects among constituents. Integrating biochemometrics with dereplication and compound annotation approaches via GNPS-based molecular networking has accelerated the discovery of novel chemical scaffolds with biological potential. This review offers a chronological assessment of biochemometrics in natural product research, critically examining its evolution from the inception of the concept, development in the field, to its present applications in natural product research. It outlines its diverse applications across plant, microbial, and marine natural product sources, highlighting key case studies that demonstrate its utility across different natural product sources for the identification of bioactive compounds. By evaluating its strengths and limitations, this review underscores the critical importance of rigorous data acquisition and preprocessing as critical steps inherent to the success of biochemometric modeling. Model validation is considered equally important to ensure the robustness and accuracy of the derived projections. As omics continue to advance with sophisticated analytical and computational techniques, the review also identifies emerging opportunities for integrating biochemometrics with GNPS-based molecular networking, and employing dereplication via NP databases and artificial intelligence. These integrated approaches enhance predictive modeling and pattern recognition, enable dereplication with global natural product databases, and streamline prioritization of bioactive natural products. Together, the biochemometrics and its advancements will accelerate the discovery of novel bioactive natural products and support the development of next-generation natural product-based therapeutic drugs.