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

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.