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<p>Our study systematically explored the novel biochemical groups and compounds from the extracts of moss <i>Barbula constricta</i> (Mitt.) using FTIR and GC-MS techniques coupled with network pharmacology and molecular docking studies to access the underlying molecular mechanism of selected compounds against inflammation. FTIR revealed important chemical groups such as hydroxyl, aldehyde, alkenes, aromatic, carbonyl and aliphatic alkenes. A total of 16 chemical compounds were tentatively identified using GC-MS technique. Out of 16 compounds, Ergost-5-en-3-ol and Stigmasterol were selected based on ADME screening for network analysis and molecular docking studies. Further top 10 anti-inflammatory hub genes named SRC, PTGS2, MAPK3, CYP3A4, ESR1, PPARA, NR3C1, HMGCR, CYP19A1, PGR were identified and most important protein i.e., SRC with the highest degree of interaction was selected to visualize and interpret its docking efficiency with identified bioactive compounds. Molecular docking analysis revealed ligand Stigmasterol has good binding efficacy towards SRC with a docking score of -9.4&#xa0;kcal/mol as compared to control anti-inflammatory drug Dasatinib. These findings are derived from in-silico predictions, further in vitro and in vivo studies are necessary to validate their efficacy.</p>

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Characterization of moss Barbula constricta (Mitt.) by comprehensive FTIR/ GC-MS-based metabolomics coupled with network pharmacology and molecular docking revealed potential anti-inflammatory compounds

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月16日

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  • Shiwani Latwal,
  • Anju Rao

摘要

Our study systematically explored the novel biochemical groups and compounds from the extracts of moss Barbula constricta (Mitt.) using FTIR and GC-MS techniques coupled with network pharmacology and molecular docking studies to access the underlying molecular mechanism of selected compounds against inflammation. FTIR revealed important chemical groups such as hydroxyl, aldehyde, alkenes, aromatic, carbonyl and aliphatic alkenes. A total of 16 chemical compounds were tentatively identified using GC-MS technique. Out of 16 compounds, Ergost-5-en-3-ol and Stigmasterol were selected based on ADME screening for network analysis and molecular docking studies. Further top 10 anti-inflammatory hub genes named SRC, PTGS2, MAPK3, CYP3A4, ESR1, PPARA, NR3C1, HMGCR, CYP19A1, PGR were identified and most important protein i.e., SRC with the highest degree of interaction was selected to visualize and interpret its docking efficiency with identified bioactive compounds. Molecular docking analysis revealed ligand Stigmasterol has good binding efficacy towards SRC with a docking score of -9.4 kcal/mol as compared to control anti-inflammatory drug Dasatinib. These findings are derived from in-silico predictions, further in vitro and in vivo studies are necessary to validate their efficacy.