Rapid Targeted Screening and Identification of Active Ingredients in Herbal Extracts through Ligand-Detected NMR and Database Matching

Herbal extracts are rich sources of active compounds that can be used for drug screening due to their diverse and unique chemical structures. However, traditional methods for screening these compounds are notably laborious and time-consuming. In this manuscript, we introduce a new high-throughput approach that combines nuclear magnetic resonance (NMR) spectroscopy with a tailored database and algorithm to rapidly identify bioactive components in herbal extracts. This method distinguishes characteristic signals and structural motifs of active constituents in the raw extracts through a relaxation-weighted technique, particularly utilizing the perfect echo Carr-Purcell-Meiboom-Gill (peCPMG) sequence, complemented by precise 2D spectroscopic strategies. The cornerstone of our approach is a customized database designed to filter potential compounds based on defined parameters, such as the presence of CH_n segments and unique chemical shifts, thereby expediting the identification of promising compounds. This innovative technique was applied to identifying substances interacting with choline kinase α (ChoKα1), resulting in the discovery of four new inhibitors. Our findings demonstrate a powerful tool for unraveling the complex chemical landscape of herbal extracts, considerably facilitating the search for new pharmaceutical candidates. This approach offers an efficient alternative to traditional methods in the quest for drug discovery from natural sources.