Evidence map›Paper›PMID 41402335›Full record

ArticleScientific reports2025

Computational drug repositioning approach to predict multi-target therapeutics for epilepsy.

Pawan Kumar, Vivek Kumar, Raveena Chauhan, Vandana Saini, Ajit Kumar

Abstract read
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

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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

5 authors.

Pawan KumarToxicology and Computational Biology Group, Centre for Bioinformatics, Maharshi Dayanand University, Rohtak, Haryana, 124001, India.
Vivek KumarToxicology and Computational Biology Group, Centre for Bioinformatics, Maharshi Dayanand University, Rohtak, Haryana, 124001, India.
Raveena ChauhanToxicology and Computational Biology Group, Centre for Bioinformatics, Maharshi Dayanand University, Rohtak, Haryana, 124001, India.
Vandana SainiToxicology and Computational Biology Group, Centre for Bioinformatics, Maharshi Dayanand University, Rohtak, Haryana, 124001, India.
Ajit KumarToxicology and Computational Biology Group, Centre for Bioinformatics, Maharshi Dayanand University, Rohtak, Haryana, 124001, India. akumar.cbt.mdu@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epilepsy affects millions of people globally, with approximately one-third of patients experiencing drug-resistant seizures. Developing new anti-epileptic drugs is time-intensive and costly, prompting interest in computational drug repositioning strategies. Here, we report on a comprehensive drug repositioning approach to identify the multi-targeted therapeutic option(s) for epileptic seizures. All approved drugs from the DrugBank database were screened for their anti-epileptic properties, which involved predicting their blood-brain permeability and clustering them based on structural similarity with marketed anti-epilepsy drugs. The screened drugs were subjected to molecular docking against previously identified therapeutic target proteins (Voltage-Gated Sodium Channel α2; GABA receptor α1-β1; and Voltage-Gated Calcium Channel α1G), A total of 46 drugs showed better binding affinity than the respective standard drugs - Carbamazepine, Clonazepam and Pregabalin for the selected target proteins - Voltage-Gated Sodium Channel α2; GABA receptor α1-β1; and Voltage-Gated Calcium Channel α1G, respectively. The binding pocket and literature data mining revealed three drugs, Oxaprozin, Pizotifen, and Cyproheptadine, that bind within the precise binding pocket and have no reported severe side effects related to seizure onset. The molecular dynamics simulation studies revealed that all three compounds exhibited more stable and better binding interactions with their corresponding drug targets. Oxaprozin, among the identified three drugs, showed a very stable binding and can be considered a potential repurposed drug for epilepsy, warranting further preclinical trials.

Indexed as

AnticonvulsantsDrug RepositioningEpilepsyBinding SitesComputational BiologyHumansMolecular Docking SimulationMolecular Dynamics SimulationAnticonvulsantsAEDDrug repurposing/RepositioningEpilepsyMolecular dockingMolecular dynamic simulationsSeizures

Identifiers

PMID41402335
PMCPMC12708636

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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 OpenQuestion graph.