Clinical side-effects based drug repositioning for anti-epileptic activity

Abstract

Several generations of anti-epileptic drugs (AEDs) are available but have several associated side effects apart from a limited success rate. Drug repositioning strategies have gained importance in the last two decades owing to lower failure rates and economic burden. Drugs with similar side effect profiles may share a common mechanism of action and thus can be linked to other disease treatments. The present study was carried out to identify the newly approved drug candidate(s) as AEDs using clinical side-effects drug repositioning strategy. The clinical side effect similarity of drugs available in the SIDER v4.1 database was estimated against common side effects of 5 major marketed AEDs, using the ‘dplyr’ package library in the R. Further drugs were filtered based on Blood Brain Barrier permeability prediction and FDA-approval status. Molecular docking studies were performed for selected 26 hits (drugs) against previously identified epilepsy target receptors: Voltage-gated sodium channel α2 (Nav1.2), GABA receptor α1-β1 (GABAr α1-β1), and Voltage-gated calcium channel α-1 G (Cav3.1). Only 2 drugs (Ziprasidone and Paroxetine) showed better binding affinities against studied epilepsy receptors Nav1.2, GABAr α1-β1, and Cav3.1, than their corresponding standard AEDs, i.e. Carbamazepine, Clonazepam, and Pregabalin, respectively. Ziprasidone reportedly showed seizure-like symptoms in ∼3% of patients and was hence omitted from further study. The MDS study of docked complexes of Paroxetine with selected epilepsy target receptors showed stable RMSD values and better interaction energies. The study reveals Paroxetine as a potential candidate to be repurposed for 1st line epileptic seizure medication.

Communicated by Ramaswamy H. Sarma

Keywords:

• Epilepsy
• drug repositioning
• side-effect-based drug repositioning
• molecular modelling
• molecular docking study
• molecular dynamic simulation

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author wishes to acknowledge the Council of Scientific and Industrial Research (CSIR), New Delhi, India, for supporting financial assistance to Pawan Kumar as a Senior Research Fellowship. The author also thanks the DBT-BUILDER Grant of M. D. University, Rohtak, for extending the lab facility and High-performance computing (HPC) facility ‘Param Smriti’, NABI, Mohali for the super-computational facility.