Bioinformatic analysis of missense SNPs in the KCNJ10 gene associated with neurological disorders

Abstract Background Neurological disorders demonstrate significant heterogeneity influenced by genetic factors such as single-nucleotide polymorphisms (SNPs). The KCNJ10 gene plays an essential role in potassium ion homeostasis in various cell types, especially within the glial cells of the central nervous system, and houses SNPs that contribute to neurological disorders including the EAST/SeSAME syndrome and autism spectrum disorders. Given the resource-intensive nature of experimentally elucidating the impact of each SNP and the multitude of variants, bioinformatics tools provide alternatives for identifying harmful missense SNPs and predicting their clinical implications. Method Information about genes and proteins was obtained from databases (NCBI, GeneCards, UniProt). SIFT, PolyPhen-2, SNPs&GO, PhD-SNP, SNAP2, PANTHER-PSEP, and Meta-SNP software tools were used to predict possible deleterious effects of missense SNPs. I-Mutant 2.0 and MUpro were used to estimate protein stabilization effects. Additionally, Project HOPE was used to analyze the effects of variants on protein structure. Additionally, gene–gene interactions were analyzed with the GeneMANIA software tool. Results Employing bioinformatics tools like SIFT, PolyPhen-2, SNPs&GO, PhD-SNP, SNAP2, PANTHER-PSEP, and Meta-SNP, several harmful SNPs in the KCNJ10 gene were pinpointed, including rs387906834 (R65S), rs374746230 (F181L), rs373270208 (F82S), rs368857205 (R134H), rs137853072 (G77R), rs137853071 (R297C), rs137853068 (C140R), rs137853066 (R65P), rs17853258 (G83V), rs1130182 (L166P), and rs1130182 (L166Q). In the protein stabilization results of these variants, all variants except one were found to reduce protein stabilization. Conclusion The identified harmful missense SNPs within the KCNJ10 gene, and their consequent influence on protein stability and physicochemical properties, emphasize the importance of this gene in the realm of neurological disorders. Leveraging bioinformatics tools helps in subsetting a vast array of SNPs and is indispensable for prioritizing specific SNPs in future experimental and clinical research.