Department of Bioinformatics and Computational Biology, George Mason University, Fairfax, VA, USA.
Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali, Bangladesh.
J Biomol Struct Dyn. 2022;40(21):11173-11189. doi: 10.1080/07391102.2021.1957714. Epub 2021 Aug 6.
In humans, the dimeric receptor complex IFNAR2-IFNAR1 accelerates cellular response triggered by type I interferon (IFN) family proteins in response to viral infection including Coronavirus infection. Studies have revealed the association of the gene with severe illness in Coronavirus infection and indicated the association of genomic variants, i.e. single nucleotide polymorphisms (SNPs). However, comprehensive analysis of SNPs of the gene has not been performed in both coding and non-coding region to find the causes of loss of function of IFNAR2 in COVID-19 patients. In this study, we have characterized coding SNPs (nsSNPs) of gene using different bioinformatics tools and identified deleterious SNPs. We found 9 nsSNPs as pathogenic and disease-causing along with a decrease in protein stability. We employed molecular docking analysis that showed 5 nsSNPs to decrease binding affinity to IFN. Later, MD simulations showed that P136R mutant may destabilize crucial binding with the IFN molecule in response to COVID-19. Thus, P136R is likely to have a high impact on disrupting the structure of the IFNAR2 protein. GTEx portal analysis predicted 14 sQTLs and 5 eQTLs SNPs in lung tissues hampering the post-transcriptional modification (splicing) and altering the expression of the gene. sQTLs and eQTLs SNPs potentially explain the reduced IFNAR2 production leading to severe diseases. These mutants in the coding and non-coding region of the gene can help to recognize severe illness due to COVID 19 and consequently assist to develop an effective drug against the infection.Communicated by Ramaswamy H. Sarma.
在人类中，二聚体受体复合物 IFNAR2-IFNAR1 可加速细胞对 I 型干扰素（IFN）家族蛋白的反应，以响应病毒感染，包括冠状病毒感染。研究表明，该基因与冠状病毒感染的严重疾病有关，并表明基因组变异（即单核苷酸多态性（SNP））与该基因有关。然而，尚未在编码和非编码区域对 IFNAR2 基因的 SNP 进行全面分析，以寻找 COVID-19 患者 IFNAR2 功能丧失的原因。在这项研究中，我们使用不同的生物信息学工具对 基因的编码 SNP（nsSNP）进行了表征，并鉴定了有害 SNP。我们发现了 9 个 nsSNP 是致病性的，并导致蛋白稳定性降低。我们进行了分子对接分析，表明 5 个 nsSNP 降低了与 IFN 的结合亲和力。随后，MD 模拟表明 P136R 突变体可能破坏与 IFN 的关键结合，以响应 COVID-19。因此，P136R 可能会对 IFNAR2 蛋白的结构产生重大影响。GTEx 门户分析预测了肺组织中的 14 个 sQTLs 和 5 个 eQTLs SNP，这些 SNP 会干扰转录后修饰（剪接）并改变 基因的表达。sQTLs 和 eQTLs SNP 可能解释了 IFNAR2 产生减少导致严重疾病的原因。这些编码和非编码区域的突变体可帮助识别因 COVID-19 导致的严重疾病，并因此有助于开发针对感染的有效药物。由 Ramaswamy H. Sarma 交流。
