Computational prediction and QSAR-based design of novel curcumin derivatives: Enhancing insulin receptor binding and pharmacokinetic properties for improving therapeutic efficacy
1
Chemistry Department, Faculty of Science, Sohag University, Sohag, Egypt
2
Biotechnology Program, Faculty of Agriculture, Ain Shams University, Egypt
10.21608/bbj.2025.361161.1089
Abstract
Curcumin (CUR) demonstrates therapeutic potential for insulin resistance (IR) and type 2 diabetes through anti-inflammatory and insulin-sensitizing properties. However, clinical applications remains limited due to poor bioavailability and weak insulin receptor binding affinity. Despite extensive anti-diabetic studies, a critical gap exists in developing structurally optimized CUR-derivatives with enhanced insulin receptor binding and validated pharmacokinetic profiles. This study aims to design novel CUR- derivatives with improved insulin receptor interactions using integrated computational approaches. A comprehensive framework combining molecular docking, QSAR modelling, and ADMET profiling evaluated ten CUR-derivatives. Molecular docking simulations against insulin (PDB ID: 6JK8) and insulin receptor (PDB ID: 4ZXB) used AutoDock Vina, with genetic algorithm-based optimization guiding rational design. CUR-Derivatives demonstrated substantially improved binding affinities versus native CUR:-7.16 to -9.98 kcal/mol (insulin) and -7.86 to -10.49 kcal/mol (insulin receptor) compared to -6.81 and -5.03 kcal/mol, respectively. CUR-3 emerged as the lead candidate with superior binding affinity (-9.98/-10.49 kcal/mol), balanced ADMET properties (LogP = 3.876, LogS = -3.729), and favorable safety profile. QSAR analysis (R² ≈ 1, Q² = 0.75) identified moderate lipophilicity and balanced hydrogen bonding as critical activity determinants.CUR-3 represents a promising scaffold for anti-diabetic therapeutics requiring experimental validation to confirm therapeutic potential for IR management.
Kadry, A., Soliman, A., & Abbas, M. (2025). Computational prediction and QSAR-based design of novel curcumin derivatives: Enhancing insulin receptor binding and pharmacokinetic properties for improving therapeutic efficacy. Biological and Biomedical Journal, 3(2), 73-78. doi: 10.21608/bbj.2025.361161.1089
MLA
Asmaa M. Kadry; Ahmed G. Soliman; Mounir M. Abbas. "Computational prediction and QSAR-based design of novel curcumin derivatives: Enhancing insulin receptor binding and pharmacokinetic properties for improving therapeutic efficacy", Biological and Biomedical Journal, 3, 2, 2025, 73-78. doi: 10.21608/bbj.2025.361161.1089
HARVARD
Kadry, A., Soliman, A., Abbas, M. (2025). 'Computational prediction and QSAR-based design of novel curcumin derivatives: Enhancing insulin receptor binding and pharmacokinetic properties for improving therapeutic efficacy', Biological and Biomedical Journal, 3(2), pp. 73-78. doi: 10.21608/bbj.2025.361161.1089
VANCOUVER
Kadry, A., Soliman, A., Abbas, M. Computational prediction and QSAR-based design of novel curcumin derivatives: Enhancing insulin receptor binding and pharmacokinetic properties for improving therapeutic efficacy. Biological and Biomedical Journal, 2025; 3(2): 73-78. doi: 10.21608/bbj.2025.361161.1089
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