Integrated computational strategies for Polypharmacological profiling and identification of anti-inflammatory targets in Rungia pectinata L

用于 Rungia pectinata L 多药理学分析和抗炎靶点鉴定的综合计算策略

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Abstract

Rungia pectinata L. is an ethnomedicinal herb belonging to the Acanthaceae family and it presents a promising avenue for medicinal exploration, deeply rooted in traditional practices. Earlier research has demonstrated that the herb can effectively relieve the classic symptoms of inflammation. Nevertheless, comprehensive studies into the mechanisms underlying R. pectinata's beneficial impact on inflammation pathways, remain scarce. Hence, we employed an integrated approach combining network pharmacology, molecular docking and molecular dynamics simulations to explore the mechanisms underlying R. pectinata's anti-inflammatory activity. For this study, seven inflammation-related active ingredients were identified among 38 candidates, revealing 22 intersecting genes associated with inflammation. Protein-protein interaction (PPI) networks revealed three therapeutic targets: IL1B, PTGS2 and SRC. GO and KEGG pathway enrichment analyses indicated that the effects of R. pectinata are mediated by genes related to inflammation and cancer. Molecular docking studies identified trans-nerolidyl formate and widdrol as lead compounds while molecular dynamics simulations indicated stable compound-target complexes, with MM-PBSA calculations showing superior free energy values for SRC, suggesting implications in cancer pathways. Overall, this study offers valuable insights into the anti-inflammatory effects of R. pectinata, which may be mediated through key pathways involved in inflammation and cancer. This highlights the potential of R. pectinata in both anti-inflammatory and anticancer therapies. However, further experimental validation is necessary to confirm these findings.

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