Bioinformatic approaches were utilized to investigate the pattern of codon usage in 109 epilepsy-related genes. The genes were found to be rich in G and C nucleotides, with GC usage 7% higher than AT. Preferred codon analysis confirmed the dominance of G and C at the wobble position of codons. CAG is the most frequently used codon. The ENc analysis, on the other hand, did not reveal any exceptional codon usage bias. Correlation of GC content at the first and second codon positions with the third codon position (neutrality plot) suggested the impact of selection pressure in shaping the GC enriched compositional pattern observed in epilepsy-related genes. It was further confirmed by correspondence analysis. Altogether, our findings imply that the pattern of evolutionary processes (especially selection pressure) operating on epilepsy-related genes. This might aid in identifying disease genes compositional signatures and deciphering the genetic mechanisms underlying epilepsy. Further this information would be useful in facilitating the existing epilepsy related therapies like gene therapy, cell therapy etc.