Computational-experimental identification of bioactive component combinations from Salvia miltiorrhiza for...

Cardiovascular dysfunction represents a major global health challenge due to its high morbidity and mortality, underscoring the urgent need for more efficient drug discovery paradigms. This study developed and applied an integrative computational-experimental strategy to systematically explore and prioritize bioactive component combinations with crude extract-comparable activity (BECC) from traditional herbs, using Salvia miltiorrhiza (Danshen, DS) as a representative case relevant to cardiovascular protection. LC-MS/MS-based exposure-informed metabolite profiling, reverse target fishing, molecular docking, pharmacophore analysis were integrated to develop multidimensional component-target networks. Through this framework, 139 potential targets associated with 26 bioactive components and 41 metabolites were collected. Target activity spectrum (TAS) and pharmacodynamic activity spectrum (PAS) analyses were further employed to prioritize BECC, comprising rosmarinic acid, salvianolic acids A and B, cryptotanshinone, and tanshinone I. Within the tested in vitro systems and concentration ranges, this combination exhibited pharmacological activity profiles that were broadly comparable to those of the crude DS extract, as evaluated in three cardiovascular-relevant cellular models, supporting its potential as a representative multi-component candidate. In conclusion, this study provides a proof-of-concept case study demonstrating an integrative strategy to narrow complex herbal extracts into defined component combinations for subsequent translational evaluation, offering a methodological reference for studying the multi-component basis of traditional medicines in the context of cardiovascular-related research.