Salvia miltiorrhiza for Viral Myocarditis: Multi-Computational Pharmacological Exploration and Meta-Analytic Efficacy...

Viral myocarditis (VMC) is the predominant type of myocarditis and currently lacks specific therapies. Salvia miltiorrhiza (Danshen) injection has demonstrated beneficial effects as a supplementary VMC treatment, yet its pharmacological mechanisms are ambiguous, and its efficacy lacks robust evidence. This study aims to preliminarily address these issues through computational approaches and meta-analysis. Using network pharmacology, we identified 257 therapeutic targets, 106 hub genes, and 4 key S. miltiorrhiza ingredients implicated in VMC treatment. Integrating transcriptome data with LASSO and SVM machine learning algorithm yielded six core therapeutic targets from the hub genes-TNF, JUN, PECAM1, KDR, TIMP1, and EPAS1-which are primarily associated with anti-inflammatory activity, vascular remodeling, and fibrosis suppression. GO analysis identified the "inflammatory response" as the most prominent biological process. Concurrently, the PI3K-Akt, TNF, and HIF-1 signaling pathways-each closely associated with inflammation-appeared among the top 20 KEGG pathways. Overall, these results indicate that suppressing excessive inflammation is likely the primary pharmacological mechanism. In molecular docking, four key ingredients-dan-shexinkum D, danshenol A, cryptotanshinone, and methylrosmarinate-exhibited strong binding to the core therapeutic targets, with dan-shexinkum D showing the lowest total binding energy and stable binding confirmed by molecular dynamics simulations. The meta-analysis indicates that S. miltiorrhiza injection improves clinical outcomes and significantly reduces TNF-α, hs-CRP, CK-MB, cTnT, and H-FABP levels. This study used multiple computational approaches to explore the pharmacological mechanisms and identify key active components of S. miltiorrhiza in treating VMC, thereby establishing an evidence-based foundation and providing preliminary groundwork for subsequent clinical application and translational research.