Network Pharmacology and Experimental Validation to Reveal the Pharmacological Mechanisms of Liuwei Dihuang Decoction Against Intervertebral Disc Degeneration

To explore the pharmacological mechanisms of Liuwei Dihuang Decoction (LWDHD) against intervertebral disc (IVD) degeneration (IVDD) via network pharmacology analysis combined with experimental validation. First, active ingredients and related targets of LWDHD, as well as related genes of IVDD, were collected from public databases. The protein-protein interaction (PPI) network, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed to predict the core targets and pathways of LWDHD against IVDD. Secondly, the IVDD model of mice treated with LWDHD was selected to validate the major targets predicted by network pharmacology. By searching the intersection of the active ingredient targets and IVDD targets, a total of 110 targets matched the related targets of 30 active ingredients in LWDHD and IVDD were retrieved. PPI network analysis indicated that 17 targets, including Caspase-3, IL-1β, P53, etc., were hub targets. GO and KEGG enrichment analyses showed that the apoptosis pathway was enriched by multiple targets and served as the target for in vivo experimental study validation. The results of animal experiments revealed that LWDHD administration not only restored the decrease in disc height and abnormal degradation of matrix metabolism in IVDD mice but also reversed the high expression of Bax, Caspase-3, IL-1β, P53, and low expression of Bcl-2, thereby inhibiting the apoptosis of IVD tissue and ameliorating the progression of IVDD. Using a comprehensive network pharmacology approach, our findings predicted the active ingredients and potential targets of LWDHD intervention for IVDD, and some major target proteins involved in the predictive signaling pathway were validated experimentally, which gave us a new understanding of the pharmacological mechanism of LWDHD in treating IVDD at the comprehensive level.