Title:In-silico Identification and Analysis of Hub Proteins for Designing Novel
First-line Anti-seizure Medications
Volume: 20
Issue: 6
Author(s): Pawan Kumar, Deepak Sheokand, Vandana Saini and Ajit Kumar*
Affiliation:
- Toxicology & Computational Biology Group, Centre for Bioinformatics, M. D. University, Rohtak, 124001 India
Keywords:
Epilepsy, mechanism of action, network biology, protein-protein interaction, FDA, STRING.
Abstract:
Background: Epilepsy is a seizure-related disease with different symptoms and types, depending
on the origin and propagation region of the brain. There are several marketed anti-seizure medications
(ASMs) available for choice of treatment by clinicians but there is a huge paucity of ideal first-line
ASMs.
Objective: The present study was undertaken to identify and get an insight into the major target (hub)
proteins, which can be comprehensively used as a platform for designing first-line ASMs.
Methods: Large-scale text mining was done to generate a data warehouse of available ASMs and their
MOAs, followed by the identification of specific isoforms of target proteins for designing next-generation
ASMs, using network biology and other in-silico approaches.
Results: The study resulted in the identification of 3 major classes of target proteins of major ASMs and
their specific isoforms, namely – GABA receptors (GABRA1, GABRB1, and GABARAP); VGSC (α-
subunitSCN2A (Nav1.2)) and VGCC (α-subunitCACNA1G (Cav3.1)). The identified proteins were also
observed to be concurrent with the target sites of majorly sold ASMs currently.
Conclusion: The predicted hub protein families and their specific isoforms can be further validated and
comprehensively used to design next-generation novel first-line ASM(s).