Integrative strategies in herbal product-based Drug discovery: from computational models to molecular insights

Abstract

Conventional drug discovery process is associated with high costs, lengthy development timelines, and high failure rates mainly for complex multifactorial diseases. These challenges highlight the existing need for various innovative discovery strategies. Natural product continues to play an important role in discovery of drugs, with natural compounds and their derivatives accounting for approximately one-third of all small-molecule drugs that were approved from 1981 to 2019. Currently, computational and systems-based approaches are being increasingly incorporated in various steps of herbal-drug discovery. These approaches include molecular docking, virtual screening, quantitative structure-activity relationship (QSAR) modelling, network pharmacology, and bioactivity prediction using machine learning. Other emerging technologies such as genome editing and synthetic biology also provide additional opportunities to access and optimize valuable natural-product metabolites. Together, these tools can aid in identifying candidate molecules, elucidate potential mechanisms, and formulation development, although all of it requires experimental validation. Herbal medicines can modulate multiple molecular targets, hence can be advantageous for complex diseases. Analytical techniques such as hyphenated spectroscopy and metabolomics can further contribute to standardization and quality control. Nanocarrier systems and pharmacogenomic approaches can increase bioavailability and support more personalized therapeutic strategies. This review highlights integrated approaches for improving discovery, validation, and herbal therapeutic development. The combination of traditional knowledge with computational and analytical approaches provides a practical framework for herbal product-based drug discovery. Continued progress will depend on standardization, reproducible methodologies, and robust clinical evidence.