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<p>Optimizing the potency of kinase inhibitors remains a major challenge due to the structural conservation of kinase binding pockets. While several computational methods have been developed to address this issue, most overlook the crucial role of water molecules within the binding site. Our research aims to address this gap by examining topological water networks (TWNs) within the target protein. We identified specific TWN-derived patterns in kinase binding sites which align with known crystallographic kinase fragments. Our findings reveal the potential of TWNs to significantly improve the identification and optimal placement of promising fragments within protein binding sites. Here, we propose TWN-based fragment growing (TWN-FG) method that enhances kinase inhibitor potency by leveraging the topological characteristics of hydration networks. TWN-FG successfully explains structure–activity relationship (SAR) trends of known kinase inhibitors and has been applied to design and synthesize a potent mixed lineage kinase 1 (MLK1) inhibitor. The source code is available at <a href="https://github.com/RgJeoung/TWN-FG">https://github.com/RgJeoung/TWN-FG</a> to support further research and application.</p>

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A novel approach for enhancing the potency of kinase inhibitors using topological water networks

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月31日

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  • Re Gin Jeoung,
  • Anand Balupuri,
  • Nayoung Lim,
  • Sungwook Choi,
  • Nam Sook Kang

摘要

Optimizing the potency of kinase inhibitors remains a major challenge due to the structural conservation of kinase binding pockets. While several computational methods have been developed to address this issue, most overlook the crucial role of water molecules within the binding site. Our research aims to address this gap by examining topological water networks (TWNs) within the target protein. We identified specific TWN-derived patterns in kinase binding sites which align with known crystallographic kinase fragments. Our findings reveal the potential of TWNs to significantly improve the identification and optimal placement of promising fragments within protein binding sites. Here, we propose TWN-based fragment growing (TWN-FG) method that enhances kinase inhibitor potency by leveraging the topological characteristics of hydration networks. TWN-FG successfully explains structure–activity relationship (SAR) trends of known kinase inhibitors and has been applied to design and synthesize a potent mixed lineage kinase 1 (MLK1) inhibitor. The source code is available at https://github.com/RgJeoung/TWN-FG to support further research and application.