ORIGINAL RESEARCH article
Front. Bioinform.
Sec. Drug Discovery in Bioinformatics
This article is part of the Research TopicBioinformatics, Drug Discovery, and PlantsView all articles
Machine Learning-Based QSAR and Molecular Modeling of Phytocompounds in Barleria buxifolia L. as a Potential Aldose Reductase Inhibitor
Provisionally accepted
- Centre for Integrative Omics Data Science (CIODS), Yenepoya University, Mangalore, India
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The traditional medicinal plant Barleria buxifolia L is well-known for its pharmacological properties. This study aims to predict the binding affinity of bioactive compounds obtained from B. buxifolia towards significant molecular targets associated with diabetes mellitus. The polyol pathway enzyme aldose reductase is associated with diabetes, making it a possible therapeutic target. By redocking the co-crystallised ligand sulindac sulfone into the aldose reductase binding site, the researchers proved the docking approach's reliability with a 0.117 Å root mean square deviation (RMSD). Virtual screening showed that 9-Carbomethoxy-6,11-dichloroxy-5-oxoxantho[3,2-g] tetralin (9CDOT) as a promising inhibitor, surpassing sulindac sulfone, which had a glide score of -9.95 kcal/mol and binding energy of -55.10 kcal/mol. The chosen molecule exhibited significant binding affinity through π–π interactions with Trp111 and Trp219, a stabilising hydrogen bond with Leu300, and hydrophobic contacts with Val297, Ala299, and Leu300. Halogen bonding connections were found with one chlorine facing Trp219, suggesting π-halogen interaction, and the other towards Leu300 and Leu301, indicating halogen-hydrophobic stabilisation. Synergistic interactions increase ligand target site affinity and specificity. The compound was non-hepatotoxic, non-neurotoxic, and non-cytotoxic, according to the toxicity prediction. Our investigation shows that 9CDOT, a phytocompound from B. buxifolia, strongly inhibits human aldose reductase. The molecule is considered to be one of B. buxifolia's active antidiabetic principles, making it a promising aldose reductase inhibitor lead candidate. Further verifying its potency, an AI-assisted PCA–PLS QSAR model also showed high predictive performance (R2 = 0.692), with 9CDOT showing a projected pIC₅₀ of 7.52 (IC₅₀=30 nM). To determine its therapeutic efficacy and investigate its potential as a lead candidate for the management of diabetes complications, more experimental validation is required.
Keywords: aldose reductase, antidiabetic, Barleria buxifolia L, molecular docking, molecular dynamics, Toxicity prediction
Received: 12 Dec 2025; Accepted: 16 Feb 2026.
Copyright: © 2026 Dev, Lalu, Zarin, Joseph, Raju, J and Thekkan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Abhithaj J
Sangeeth Thekkan
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