Unveiling Molecular Basis of Terminalia chebula in Modulating the AGE-RAGE-PRKCB Axis in Diabetic Nephropathy: Integrative Network Pharmacology and Computational Study
- 1Department of Biochemistry and Molecular Biology, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh
- 2Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh
Abstract
Diabetic nephropathy (DN), a progressive microvascular complication of diabetes, remains a principal cause of renal failure worldwide, yet its multifaceted molecular complexity continues to challenge effective therapeutic intervention. In this study, an integrative network pharmacology and computational modeling framework was employed to unravel the mechanistic basis of Terminalia chebula in mitigating DN pathology. A total of 357 phytoconstituents were retrieved from the IMPPAT 2.0 and PubChem databases and screened through SwissADME and pkCSM, yielding 14 bioactive, drug-like, and non-toxic compounds. Target prediction integrated data from SwissTargetPrediction, BindingDB, and CTD, while DN-related genes were compiled from GeneCards, OMIM, and transcriptomic datasets (GSE154561, GSE154881, GSE217709, and GSE30528). Overlapping targets were analyzed using STRING and Cytoscape to identify key hub proteins, followed by Gene Ontology (GO) and KEGG enrichment analysis. Integration of compound- and disease-associated targets identified 173 overlapping genes. Enrichment analyses revealed significant involvement in the AGE–RAGE signaling pathway, implicating PRKCB as a key regulatory node linking hyperglycemia to oxidative stress, inflammation, and apoptosis. The Random Forest-based QSAR model (R2 = 0.91, RMSE = 0.41) denoted Luteolin and Quercetin as potent PRKCB inhibitors (predicted pIC₅₀ ≥ 6). Docking and molecular dynamics simulations confirmed stable PRKCB binding (RMSD ≤ 3.0 Å; ΔG_bind ≈ –122 kcal/mol), supported by DFT analysis indicating high chemical softness and strong charge-transfer potential. This integrative computational analysis suggests that T. chebula may exert renoprotective effects through modulation of the PRKCB-driven AGE-RAGE axis, with luteolin and quercetin emerging as promising natural inhibitors. Therefore, these computational findings provide potential molecular insight into the traditional therapeutic efficacy of T. chebula and a foundation for further experimental validation in DN.
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BibTeX
@article{niaz2026unveiling,
title = {{Unveiling Molecular Basis of Terminalia chebula in Modulating the AGE-RAGE-PRKCB Axis in Diabetic Nephropathy: Integrative Network Pharmacology and Computational Study}},
author = {S. M. Riaduzzaman Niaz and Sumaia Jannat and Sheikh Abdullah Al Ashik and Md. Khairul Islam},
journal = {PLOS One},
year = {2026},
month = nov,
doi = {10.1371/journal.pone.0362295},
url = {https://doi.org/10.1371/journal.pone.0362295},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Unveiling Molecular Basis of Terminalia chebula in Modulating the AGE-RAGE-PRKCB Axis in Diabetic Nephropathy: Integrative Network Pharmacology and Computational Study
AU - S. M. Riaduzzaman Niaz
AU - Sumaia Jannat
AU - Sheikh Abdullah Al Ashik
AU - Md. Khairul Islam
PY - 2026
DA - 2026/11/05
JO - PLOS One
DO - 10.1371/journal.pone.0362295
UR - https://doi.org/10.1371/journal.pone.0362295
AB - Diabetic nephropathy (DN), a progressive microvascular complication of diabetes, remains a principal cause of renal failure worldwide, yet its multifaceted molecular complexity continues to challenge effective therapeutic intervention. In this study, an integrative network pharmacology and computational modeling framework was employed to unravel the mechanistic basis of Terminalia chebula in mitigating DN pathology. A total of 357 phytoconstituents were retrieved from the IMPPAT 2.0 and PubChem databases and screened through SwissADME and pkCSM, yielding 14 bioactive, drug-like, and non-toxic compounds. Target prediction integrated data from SwissTargetPrediction, BindingDB, and CTD, while DN-related genes were compiled from GeneCards, OMIM, and transcriptomic datasets (GSE154561, GSE154881, GSE217709, and GSE30528). Overlapping targets were analyzed using STRING and Cytoscape to identify key hub proteins, followed by Gene Ontology (GO) and KEGG enrichment analysis. Integration of compound- and disease-associated targets identified 173 overlapping genes. Enrichment analyses revealed significant involvement in the AGE–RAGE signaling pathway, implicating PRKCB as a key regulatory node linking hyperglycemia to oxidative stress, inflammation, and apoptosis. The Random Forest-based QSAR model (R2 = 0.91, RMSE = 0.41) denoted Luteolin and Quercetin as potent PRKCB inhibitors (predicted pIC₅₀ ≥ 6). Docking and molecular dynamics simulations confirmed stable PRKCB binding (RMSD ≤ 3.0 Å; ΔG_bind ≈ –122 kcal/mol), supported by DFT analysis indicating high chemical softness and strong charge-transfer potential. This integrative computational analysis suggests that T. chebula may exert renoprotective effects through modulation of the PRKCB-driven AGE-RAGE axis, with luteolin and quercetin emerging as promising natural inhibitors. Therefore, these computational findings provide potential molecular insight into the traditional therapeutic efficacy of T. chebula and a foundation for further experimental validation in DN.
SN - 1932-6203
ER -