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February 2, 2026Journal of Computational Biophysics and Chemistry1 citations

Antifibrotic Potential of Scutellaria baicalensis Georgi Phytocompounds Targeting Smad3 in Pulmonary Fibrosis via In Silico Molecular Docking Network Pharmacology and Toxicity Analysis

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VKVenkatesan KarthickSaveetha UniversitySASingamoorthy AmalrajRajagiri HospitalMAMuniappan AyyanarBharathidasan University

Key Points

  • To explore the potential of Scutellaria baicalensis phytocompounds as modulators of Smad3 in pulmonary fibrosis using computational methods.
  • Conducted in silico molecular docking of 55 compounds against Smad3
  • Performed molecular dynamics simulations and MM-GBSA binding energy calculations
  • Utilized ProTox-II for toxicity prediction across multiple organ systems
  • Applied KEGG pathway enrichment for multi-target analysis
  • Identified six top compounds with strong affinity for Smad3, with binding energies ranging from -31.44 to -54.82 kcal/mol
  • Showed stability in binding interactions through molecular dynamics
  • Predicted low toxicity for most compounds, with some exceptions for specific compounds
  • Highlighted engagement of major inflammatory and profibrotic pathways like TGF-β and NF-κB

Abstract

Pulmonary fibrosis (PF) remains a life-threatening, progressive lung disease with limited therapeutic options. Smad3 signaling is recognized as a pivotal driver of fibrosis progression. Scutellaria baicalensis Georgi, a traditional Chinese medicinal plant widely used for thousands of years in China, known as Huang-Qin in Chinese medicine, has been applied historically for respiratory infections, inflammation, and liver diseases. Its roots contain bioactive flavonoids such as baicalin, baicalein, and wogonin, which exhibit anti-inflammatory, antioxidant, and antifibrotic properties, but its mechanistic impact on PF via Smad3 remains unclear. To systematically investigate the potential of S. baicalensis phytocompounds as Smad3 modulators in the context of pulmonary fibrosis, integrating molecular docking, binding free energy analysis, molecular dynamics (MD) simulation, toxicity prediction, and network pharmacology were investigated. Fifty-five S. baicalensis-derived compounds were screened using in silico molecular docking against Smad3 (1U7F). Binding stability and energetics were evaluated with MM-GBSA analyses, and a 100 ns explicit-solvent MD simulation of the top Smad3-baicalin complex revealed stable backbone RMSD and persistent binding-site contacts, further corroborated by post-MD MM-GBSA binding free energy. Toxicity risk was predicted using ProTox-II across organ/system endpoints. We used network pharmacology and KEGG pathway enrichment to understand multi-target processes and illness pathway convergence. The top six compounds 2- (methylamino) benzaldehyde, baicalein, baicalin, skullcapflavone II, wogonin, and skullcapflavone I showed strong affinity for Smad3, with MM-GBSA ΔGbind values from -31. 44 to -54. 82 kcal/mol. Hydrogen bonds and van der Waals forces were primary binding contributors. Toxicity prediction demonstrated favorable safety profiles, with low mutagenic, cytotoxic, and carcinogenic risks for most candidates; notable exceptions included higher neurotoxicity for 2- (methylamino) benzaldehyde and cardiotoxicity for wogonin. Network pharmacology showed robust engagement of inflammatory and profibrotic pathways, including TGF-β, MAPK, PI3K-Akt, NF-κB, and TNF. Integration of pathway data highlighted key nodes (NF? B1, HIF1A, MAOA) impacted by these phytocompounds. S. baicalensis flavonoids, especially wogonin, skullcapflavone II, and baicalin, exhibit strong predicted modulation of Smad3 and related pro-fibrotic pathways with acceptable toxicity risk. This systems-level study supports experimental and clinical evaluation of these phytochemicals as promising multi-target phytopharmaceutical candidates for pulmonary fibrosis treatment.

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Cite This Study

Karthick et al. (2026) studied this question.

synapsesocial.com/papers/6980ff08c1c9540dea811b0fhttps://doi.org/10.1142/s2737416526500584
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