In silico analysis of the functional and structural consequences of SNPs in human ARX gene associated with EIEE1

• Main Authors: Mujahed I. Mustafa, Naseem S. Murshed, Abdelrahman H. Abdelmoneim, Abdelrafie M. Makhawi
• Format: Article
• Language: English
• Published: Elsevier 2020-01-01
• Series: Informatics in Medicine Unlocked
• Subjects: ARX gene; Early infantile epileptic encephalopathy 1 (EIEE1); Neurologic disease; In silico analysis; SNPs
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352914820305979

Background: Early infantile epileptic encephalopathy 1 (EIEE1) is a rare but devastating neurologic disorder that displays concomitant cognitive and motor impairment, and is often presented in the first months of life with severe intellectual disability. Purpose: The objective of this study is to classify the most deleterious nsSNPs in ARX gene that may cause EIEE1 disease. Methods: Despite the reported association of ARX gene mutations with vulnerability to several neurologic conditions. There is lack of an in silico analysis on the functional and structural impacts of pathogenic nonsynonymous single nucleotide polymorphisms (nsSNPs) of the ARX at protein level. Therefore, the nsSNPs in the human ARX gene obtained from NCBI, were analyzed for their functional and structural impact using bioinformatics tools like SIFT, Polyphen, PROVEAN, I-Mutant, and MUPro. The effects of the mutations on tertiary structure of the human ARX protein were predicted using RaptorX and visualized by UCSF Chimera, while STRING was used to investigate its protein–protein interaction. Results: The results of in silico analysis revealed present of 11 mutations (L535Q, R528S, R380L, V374D, L343Q, T333N, T333S, R332H, R330H, G34R and L33P), thus significantly alter the structure of human ARX protein; that may disturb the domain which will affect the function of the protein. Conclusion: In this study, the effect of the structural and functional role of nsSNPs in the ARX gene was analyzed through several in silico methods, which revealed 11 mutations that have a possible functional and structural impact. Thus, could be used as diagnostic markers for EIEE1.