单核苷酸多态性是基因组序列中单个核苷酸水平的DNA改变的最常见形式。进行了全基因组关联研究(GWAS),以通过筛选与疾病相关的SNP来鉴定潜在的风险基因或基因组区域。最近的研究表明,SCN9A包含NaV1.7亚基,Na+通道有一个由1988个氨基酸组成的基因编码,分为4个结构域,都有6个跨膜区,主要存在于背根神经节(DRG)神经元和交感神经节神经元。多种形式的急性超敏反应,如原发性红斑,先天性镇痛,阵发性疼痛综合征与SCN9A基因多态性相关。根据这项研究,我们利用了多种计算工具,通过修饰SCN9A蛋白的结构或活性,探索了可能损害健康的nsSNP.超过14种潜在破坏性和致病的nsSNP(E1889D,L1802P,F1782V,D1778N,C1370Y,V1311M,Y1248H,F1237L,M936V,I929T,V877E,D743Y,C710W,D623H)通过多种算法鉴定,包括SNPnexus,SNAP-2,PANTHER,博士-SNP,SNP&GO,I-Mutant,和ConSurf。同源性建模,结构验证,还进行了蛋白质-配体相互作用以确认5个值得注意的取代(L1802P,F1782V,D1778N,V1311M,和M936V)。这样的nsSNP可能成为进一步研究由SCN9A功能障碍引起的各种疾病的中心。使用计算机内策略评估SCN9A遗传变异将有助于组织大规模调查并开发与这些变异相关的疾病的靶向治疗方法。
Single nucleotide polymorphisms are the most common form of DNA alterations at the level of a single nucleotide in the genomic sequence. Genome-wide association studies (GWAS) were carried to identify potential risk genes or genomic regions by screening for SNPs associated with disease. Recent studies have shown that SCN9A comprises the NaV1.7 subunit, Na+ channels have a gene encoding of 1988 amino acids arranged into 4 domains, all with 6 transmembrane regions, and are mainly found in dorsal root ganglion (DRG) neurons and sympathetic ganglion neurons. Multiple forms of acute hypersensitivity conditions, such as primary erythermalgia, congenital analgesia, and paroxysmal pain syndrome have been linked to polymorphisms in the SCN9A gene. Under this
study, we utilized a variety of computational tools to explore out nsSNPs that are potentially damaging to heath by modifying the structure or activity of the SCN9A protein. Over 14 potentially damaging and disease-causing nsSNPs (E1889D, L1802P, F1782V, D1778N, C1370Y, V1311M, Y1248H, F1237L, M936V, I929T, V877E, D743Y, C710W, D623H) were identified by a variety of algorithms, including SNPnexus, SNAP-2, PANTHER, PhD-SNP, SNP & GO, I-Mutant, and ConSurf. Homology modeling, structure validation, and protein-ligand interactions also were performed to confirm 5 notable substitutions (L1802P, F1782V, D1778N, V1311M, and M936V). Such nsSNPs may become the center of further studies into a variety of disorders brought by SCN9A dysfunction. Using in-silico strategies for assessing SCN9A genetic variations will aid in organizing large-scale investigations and developing targeted therapeutics for disorders linked to these variations.