Phytomedicine : international journal of phytotherapy and phytopharmacology · 2026
Yin-Huang-Qing-Fei-Capsule derived diosgenin and its optimized nanoconjugate target STAT3 against pulmonary fibrosis.
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Xu Wenjie, Xin Guang, Dong Yuman, Zhou Qilong, Wang Tao, Wei Zeliang, Wen Ao, Zhang Kun, Li Fan, Wang Yilan, Feng Lijuan, Xu Xinrui, Yu Xiuxian, Wan Chengyu, Li Yancen, Deng Lijing, Xu Jianxin, Huang Wen
Аннотация
BACKGROUND: Pulmonary fibrosis (PF) is a progressive, fatal interstitial lung disease with limited curative therapeutic options. Yin-Huang-Qing-Fei (YHQF) capsule is an approved clinical Chinese patent medicine with emerging preclinical evidence of potential anti-fibrotic bioactivity, yet its core anti-PF constituents, direct functional targets, and the druggability of its key active monomer remain largely uncharacterized.
PURPOSE: This study aimed to decipher the anti-PF pharmacodynamic basis of YHQF, validate its core active constituent and functional target, and optimize the druggability of the candidate monomer.
STUDY DESIGN: A randomized, controlled preclinical in vivo study was conducted, coupled with in vitro pharmacological validation, transcriptomic profiling, machine learning-based constituent screening, and genetic causal inference for target prioritization.
METHODS: The anti-PF efficacy of YHQF was verified in bleomycin (BLM)-induced mouse PF models. Core bioactive constituents were screened via LC-MS/MS and machine learning. Mendelian randomization (MR) was used for target prioritization, followed by molecular docking, molecular dynamics simulation, surface plasmon resonance (SPR) and siRNA assays for multi-dimensional target validation. Transcriptomic profiling was conducted to elucidate the STAT3-associated downstream regulatory pathways. A diosgenin-metformin nanoconjugate (DM) was rationally designed for druggability optimization.
RESULTS: YHQF significantly alleviated BLM-induced PF in mice. Diosgenin was identified as YHQF's core anti-PF constituent, with STAT3 validated as its direct functional target. Diosgenin exerted STAT3-dependent anti-fibrotic effects, and DM nanomicelles exhibited notably enhanced in vivo anti-PF efficacy.
CONCLUSION: This study defined the diosgenin-STAT3 axis as the core mechanism mediating YHQF's anti-PF effect, develops an optimized nanomedicine with improved translational potential, and provides a practical, replicable strategy for traditional Chinese medicine modernization.
PURPOSE: This study aimed to decipher the anti-PF pharmacodynamic basis of YHQF, validate its core active constituent and functional target, and optimize the druggability of the candidate monomer.
STUDY DESIGN: A randomized, controlled preclinical in vivo study was conducted, coupled with in vitro pharmacological validation, transcriptomic profiling, machine learning-based constituent screening, and genetic causal inference for target prioritization.
METHODS: The anti-PF efficacy of YHQF was verified in bleomycin (BLM)-induced mouse PF models. Core bioactive constituents were screened via LC-MS/MS and machine learning. Mendelian randomization (MR) was used for target prioritization, followed by molecular docking, molecular dynamics simulation, surface plasmon resonance (SPR) and siRNA assays for multi-dimensional target validation. Transcriptomic profiling was conducted to elucidate the STAT3-associated downstream regulatory pathways. A diosgenin-metformin nanoconjugate (DM) was rationally designed for druggability optimization.
RESULTS: YHQF significantly alleviated BLM-induced PF in mice. Diosgenin was identified as YHQF's core anti-PF constituent, with STAT3 validated as its direct functional target. Diosgenin exerted STAT3-dependent anti-fibrotic effects, and DM nanomicelles exhibited notably enhanced in vivo anti-PF efficacy.
CONCLUSION: This study defined the diosgenin-STAT3 axis as the core mechanism mediating YHQF's anti-PF effect, develops an optimized nanomedicine with improved translational potential, and provides a practical, replicable strategy for traditional Chinese medicine modernization.