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<p>Severe type-2-high asthma is driven by upstream epithelial alarmins, notably interleukin-33 signaling through the ST2 receptor, and many patients remain inadequately controlled despite optimized inhaled therapy. This study employed a comprehensive in silico discovery workflow to explore small-molecule binding at the IL-33 interaction surface of human ST2. The experimentally resolved ST2–IL-33 complex structure (PDB ID: 4KC3) was curated, and IL-33 was removed to define the receptor interaction interface, followed by binding-site identification and network-level functional analysis. A focused set of clinically relevant small molecules, together with a reference ST2-directed comparator, was retrieved from PubChem and screened using molecular docking, followed by drug-likeness, ADMET, and toxicity profiling. Zafirlukast emerged as the top-ranked scaffold with a docking score of − 7.3&#xa0;kcal/mol. A structurally optimized Zafirlukast analogue exhibited a comparable docking score of approximately − 7.0&#xa0;kcal/mol and was further examined using molecular dynamics simulations to characterize dynamic interaction behavior at the ST2 interface. MM-GBSA analysis provided qualitative insight into interaction energetics across representative simulation frames. Collectively, these results prioritize a non-biologic, ST2-directed small-molecule scaffold for further investigation and provide a computational framework to support subsequent experimental validation, including biochemical and cellular studies, in the context of severe type-2–high asthma. As this is a purely in silico study, the findings are hypothesis-generating and do not demonstrate functional inhibition of the IL-33/ST2 interaction; experimental validation is required.</p>

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In Silico identification of inhalable small-molecule IL-33/ST2 antagonists for severe type-2-high asthma endotypes

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月9日

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  • Gang Sun,
  • Qiushi Liu,
  • Miao Yu,
  • Kexing Han,
  • Lewei Huang

摘要

Severe type-2-high asthma is driven by upstream epithelial alarmins, notably interleukin-33 signaling through the ST2 receptor, and many patients remain inadequately controlled despite optimized inhaled therapy. This study employed a comprehensive in silico discovery workflow to explore small-molecule binding at the IL-33 interaction surface of human ST2. The experimentally resolved ST2–IL-33 complex structure (PDB ID: 4KC3) was curated, and IL-33 was removed to define the receptor interaction interface, followed by binding-site identification and network-level functional analysis. A focused set of clinically relevant small molecules, together with a reference ST2-directed comparator, was retrieved from PubChem and screened using molecular docking, followed by drug-likeness, ADMET, and toxicity profiling. Zafirlukast emerged as the top-ranked scaffold with a docking score of − 7.3 kcal/mol. A structurally optimized Zafirlukast analogue exhibited a comparable docking score of approximately − 7.0 kcal/mol and was further examined using molecular dynamics simulations to characterize dynamic interaction behavior at the ST2 interface. MM-GBSA analysis provided qualitative insight into interaction energetics across representative simulation frames. Collectively, these results prioritize a non-biologic, ST2-directed small-molecule scaffold for further investigation and provide a computational framework to support subsequent experimental validation, including biochemical and cellular studies, in the context of severe type-2–high asthma. As this is a purely in silico study, the findings are hypothesis-generating and do not demonstrate functional inhibition of the IL-33/ST2 interaction; experimental validation is required.