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<p>Alzheimer’s disease (AD) remains a debilitating neurodegenerative disorder with limited therapeutic options, necessitating novel approaches to target its underlying mechanisms. The NLRP3 inflammasome has emerged as a critical player in AD pathogenesis, driving neuroinflammation and amyloid-beta aggregation, yet existing inhibitors face challenges such as hepatotoxicity and poor blood-brain barrier (BBB) penetration. We conducted a computational drug repurposing study to identify FDA-approved drugs with NLRP3 inhibitory potential and favourable BBB permeability. Using molecular docking we screened a library of 2600 FDA approved compounds against the NLRP3 structure (PDB ID:8WSM), followed by molecular dynamics (MD) simulations and binding free energy calculations to validate top hits. Our results identified Flavoxates as the most promising candidate, exhibiting a high docking score (−&#xa0;10.241&#xa0;kcal/mol) and stable binding affinity (−&#xa0;52&#xa0;kcal/mol via MMPGBSA). MD simulations confirmed its robust interaction with NLRP3, demonstrating low RMSD (0.168 +/−&#xa0;0.019&#xa0;nm) and RMSF (0.088 +/−&#xa0;0.035&#xa0;nm) values over 100 ns. Moreover, Flavoxate showed optimal pharmacokinetic properties, including BBB permeability and low toxicity, as predicted by SwissADME and ProTox 3.0 The study highlights the efficacy of in silico methods in accelerating drug repurposing, bypassing the need fo de novo drug development. By repurposing Flavoxate, we propose a clinically translatable strategy to mitigate NLRP3-mediated neuroinflammation in AD, offering a potential disease modifying therapy with an established safety profile. This work underscores the significance of computational approaches in bridging the gap between preclinical discovery and therapeutic application for neurodegenerative diseases.</p>

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Computational drug repurposing identifies flavoxate as a novel NLRP3 inflammasome inhibitor for Alzheimer’s disease therapy

  • 期刊论文

  • 发表日期：

    2026年7月31日

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  • Gajendra Choudhary,
  • Harshita Rajput,
  • Rutweek Kulkarni,
  • Hadiya Siddiqui,
  • Ajay Prakash,
  • Bikash Medhi

摘要

Alzheimer’s disease (AD) remains a debilitating neurodegenerative disorder with limited therapeutic options, necessitating novel approaches to target its underlying mechanisms. The NLRP3 inflammasome has emerged as a critical player in AD pathogenesis, driving neuroinflammation and amyloid-beta aggregation, yet existing inhibitors face challenges such as hepatotoxicity and poor blood-brain barrier (BBB) penetration. We conducted a computational drug repurposing study to identify FDA-approved drugs with NLRP3 inhibitory potential and favourable BBB permeability. Using molecular docking we screened a library of 2600 FDA approved compounds against the NLRP3 structure (PDB ID:8WSM), followed by molecular dynamics (MD) simulations and binding free energy calculations to validate top hits. Our results identified Flavoxates as the most promising candidate, exhibiting a high docking score (− 10.241 kcal/mol) and stable binding affinity (− 52 kcal/mol via MMPGBSA). MD simulations confirmed its robust interaction with NLRP3, demonstrating low RMSD (0.168 +/− 0.019 nm) and RMSF (0.088 +/− 0.035 nm) values over 100 ns. Moreover, Flavoxate showed optimal pharmacokinetic properties, including BBB permeability and low toxicity, as predicted by SwissADME and ProTox 3.0 The study highlights the efficacy of in silico methods in accelerating drug repurposing, bypassing the need fo de novo drug development. By repurposing Flavoxate, we propose a clinically translatable strategy to mitigate NLRP3-mediated neuroinflammation in AD, offering a potential disease modifying therapy with an established safety profile. This work underscores the significance of computational approaches in bridging the gap between preclinical discovery and therapeutic application for neurodegenerative diseases.