In-silico Identification and Analysis of Hub Proteins for Designing Novel First-line Anti-seizure Medications

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. Method: 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).