Decoding the relationship between oxidative stress and antiseizure medications using network pharmacology and molecular docking

Oxidative stress is known to be associated with epilepsy, and antiseizure medication treatment, albeit with limited consensus on the specific oxidative stress pathways/proteins involved. Identifying these can reveal novel therapeutic targets for epilepsy management. This study utilized network pharmacology to identify potential protein targets of carbamazepine and valproic-acid that are implicated in oxidative stress and epilepsy, thereby highlighting their therapeutic potential. Drug targets for carbamazepine and valproic-acid were predicted using SuperPred/SwissTargetPrediction, while genes associated with epilepsy and oxidative stress were obtained from DisGeNET and GeneCards. Common proteins were identified, and a protein-protein interaction network was constructed using STRING, followed by analysis via Cytoscape. Hub proteins identified were EGFR, GSK3B, and STAT3 for carbamazepine, and PTGS2, mTOR, and TLR4 for valproic-acid. Molecular docking revealed a strong binding affinity of carbamazepine to its targets (ΔG<sub>bind</sub> > - 5 kcal/mol) and binding of valproic-acid to its targets (ΔG<sub>bind</sub> > - 3 kcal/mol), with PTGS2 showing the strongest interaction with valproic-acid (- 5.06 kcal/mol). These findings underscore EGFR, GSK3B, and STAT3, for carbamazepine and PTGS2, mTOR, and TLR4 for valproic-acid as pivotal therapeutic targets in oxidative stress-associated epilepsy. These identified proteins can be targeted by add on antioxidants to alleviate oxidative stress generated by chronic antiseizure medication.

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Publication Details

Journal
Scientific Reports
Published
2025-09-26
DOI
https://doi.org/10.1038/s41598-025-02884-1
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50

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article

Decoding the relationship between oxidative stress and antiseizure medications using network pharmacology and molecular docking

Anju Singh, Malhar Desai, Ritushree Kukreti, Selvaraman Nagamani et al.
1 citations
Scientific Reports
Computational Drug Discovery Methods
1.50
article

Decoding the relationship between oxidative stress and antiseizure medications using network pharmacology and molecular docking

Anju Singh, Malhar Desai, Ritushree Kukreti, Selvaraman Nagamani, Shrikant Kukreti, Sarangthem Dinamani Singh, Gurpreet Kaur Grewal, Sunik Malik
article en
1 citations

Abstract

Oxidative stress is known to be associated with epilepsy, and antiseizure medication treatment, albeit with limited consensus on the specific oxidative stress pathways/proteins involved. Identifying these can reveal novel therapeutic targets for epilepsy management. This study utilized network pharmacology to identify potential protein targets of carbamazepine and valproic-acid that are implicated in oxidative stress and epilepsy, thereby highlighting their therapeutic potential. Drug targets for carbamazepine and valproic-acid were predicted using SuperPred/SwissTargetPrediction, while genes associated with epilepsy and oxidative stress were obtained from DisGeNET and GeneCards. Common proteins were identified, and a protein-protein interaction network was constructed using STRING, followed by analysis via Cytoscape. Hub proteins identified were EGFR, GSK3B, and STAT3 for carbamazepine, and PTGS2, mTOR, and TLR4 for valproic-acid. Molecular docking revealed a strong binding affinity of carbamazepine to its targets (ΔG<sub>bind</sub> > - 5 kcal/mol) and binding of valproic-acid to its targets (ΔG<sub>bind</sub> > - 3 kcal/mol), with PTGS2 showing the strongest interaction with valproic-acid (- 5.06 kcal/mol). These findings underscore EGFR, GSK3B, and STAT3, for carbamazepine and PTGS2, mTOR, and TLR4 for valproic-acid as pivotal therapeutic targets in oxidative stress-associated epilepsy. These identified proteins can be targeted by add on antioxidants to alleviate oxidative stress generated by chronic antiseizure medication.

Scientific ReportsVol. 15(1)
University of Delhi (IN), Lovely Professional University (IN), Presidency University (IN), Institute of Genomics and Integrative Biology (IN), North East Institute of Science and Technology (IN), Govt. Dental College & Hospital (IN), Academy of Scientific and Innovative Research (IN)
Arthritis National Research Foundation, National Research Foundation, University of Delhi, Science and Engineering Research Board
Openalex Percentile: Top 13%
Computational Drug Discovery Methods
1.50
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