Evidence map›Paper›PMID 41006323›Full record

ArticleScientific reports2025

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

Malhar Desai, Sarangthem Dinamani Singh, Selvaraman Nagamani, Sunik Malik, Anju Singh, Ritushree Kukreti, Shrikant Kukreti, Gurpreet K Grewal

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Malhar DesaiDepartment of Molecular Biology and Genetic Engineering, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, Punjab, 144411, India.ORCID http://orcid.org/0000-0001-6442-6674
Sarangthem Dinamani SinghAdvanced Computation and Data Sciences Division, CSIR - North East Institute of Science and Technology, Jorhat, Assam, 785006, India.ORCID http://orcid.org/0009-0007-7809-2557
Selvaraman NagamaniAdvanced Computation and Data Sciences Division, CSIR - North East Institute of Science and Technology, Jorhat, Assam, 785006, India.ORCID http://orcid.org/0000-0002-7825-3994
Sunik MalikRT-PCR (COVID-19) Laboratory, Civil Hospital, S.B.S Nagar, Punjab, India.ORCID http://orcid.org/0009-0005-7233-6317
Anju SinghDepartment of Chemistry, Hindu College, University of Delhi, Delhi, 110007, India.ORCID http://orcid.org/0000-0003-4980-0669
Ritushree KukretiAcademy of Scientific and Innovative Research (AcSIR), Ghaziabad, India.ORCID http://orcid.org/0000-0002-6968-1129
Shrikant KukretiNucleic Acids Research Lab, Department of Chemistry, University of Delhi (North Campus), Delhi, 110007, India.ORCID http://orcid.org/0000-0002-7305-8364
Gurpreet K GrewalDepartment of Molecular Biology and Genetic Engineering, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, Punjab, 144411, India. gpkgrewal@gmail.com.ORCID http://orcid.org/0000-0002-2811-1680

Funding

Department of Science and Technology, Ministry of Science and Technology, India TAR/2022/000636
6 · The paper itself

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

Indexed as

AnticonvulsantsCarbamazepineEpilepsyMolecular Docking SimulationNetwork PharmacologyOxidative StressValproic AcidCyclooxygenase 2ErbB ReceptorsGlycogen Synthase Kinase 3 betaHumansProtein Interaction MapsSTAT3 Transcription FactorToll-Like Receptor 4TOR Serine-Threonine KinasesAnticonvulsantsCarbamazepineCyclooxygenase 2ErbB ReceptorsGlycogen Synthase Kinase 3 betaGSK3B protein, humanSTAT3 Transcription FactorToll-Like Receptor 4TOR Serine-Threonine KinasesValproic AcidAntiseizure medicationEpilepsyNetwork pharmacologyOxidative stress

Identifiers

PMID41006323
PMCPMC12475469

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.