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<p>This study explores the antidiabetic potential of <i>Turbinaria decurrens</i> marine seaweed extract loaded solid lipid nanoparticles (SLNs) targeting the TGFBR1 signalling pathway using an integrated computational and experimental approach. A Random Forest based machine learning model was developed to predict TGFBR1 inhibitory activity, achieving a prediction accuracy of 91.02%. Molecular docking analysis identified 1,2,4 triazolo[2,3 a]pyrimidine 2 carboxamide as a promising candidate with a high binding affinity of − 10.4&#xa0;kcal mol⁻¹ toward the TGFBR1 receptor, which was further confirmed through molecular dynamics simulations showing stable protein ligand interactions over a 100 ns trajectory. The seaweed extract was successfully encapsulated into solid lipid nanoparticles with an encapsulation efficiency of 94% and a loading capacity of 9.11%. Dynamic light scattering analysis indicated a particle size distribution in the range of 180 to 200&#xa0;nm with a zeta potential of approximately − 25 mV, suggesting good colloidal stability. In vitro drug release studies demonstrated controlled release behaviour following first order kinetics with improved correlation at physiological pH (R² = 0.982).Biological evaluation using 3T3 L1 adipocytes showed enhanced glucose utilization without significant cytotoxicity. In streptozotocin induced diabetic rats, treatment with SLNs resulted in significant improvement in fasting blood glucose levels, oral glucose tolerance, and serum insulin levels, along with histological recovery of pancreatic islets and protection of hepatic and renal tissues. Overall, these findings demonstrate that <i>T. decurrens</i> extract loaded SLNs represent a promising marine derived nanocarrier system for targeted modulation of the TGFBR1 pathway and potential antidiabetic therapy.</p>

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Marine Seaweed Extract Loaded Solid Lipid Nanoparticles Targeting TGFBR1 for Antidiabetic Therapy

  • 期刊论文

  • 发表日期：

    2026年5月21日

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  • Yuvaraj Dinakarkumar,
  • Panneerselvam Theivendren,
  • Sudhakar Pachiappan,
  • G. Koteswara Reddy,
  • Saravana Kumar Ganesan

摘要

This study explores the antidiabetic potential of Turbinaria decurrens marine seaweed extract loaded solid lipid nanoparticles (SLNs) targeting the TGFBR1 signalling pathway using an integrated computational and experimental approach. A Random Forest based machine learning model was developed to predict TGFBR1 inhibitory activity, achieving a prediction accuracy of 91.02%. Molecular docking analysis identified 1,2,4 triazolo[2,3 a]pyrimidine 2 carboxamide as a promising candidate with a high binding affinity of − 10.4 kcal mol⁻¹ toward the TGFBR1 receptor, which was further confirmed through molecular dynamics simulations showing stable protein ligand interactions over a 100 ns trajectory. The seaweed extract was successfully encapsulated into solid lipid nanoparticles with an encapsulation efficiency of 94% and a loading capacity of 9.11%. Dynamic light scattering analysis indicated a particle size distribution in the range of 180 to 200 nm with a zeta potential of approximately − 25 mV, suggesting good colloidal stability. In vitro drug release studies demonstrated controlled release behaviour following first order kinetics with improved correlation at physiological pH (R² = 0.982).Biological evaluation using 3T3 L1 adipocytes showed enhanced glucose utilization without significant cytotoxicity. In streptozotocin induced diabetic rats, treatment with SLNs resulted in significant improvement in fasting blood glucose levels, oral glucose tolerance, and serum insulin levels, along with histological recovery of pancreatic islets and protection of hepatic and renal tissues. Overall, these findings demonstrate that T. decurrens extract loaded SLNs represent a promising marine derived nanocarrier system for targeted modulation of the TGFBR1 pathway and potential antidiabetic therapy.