Tuberculosis and Lung Diseases Research Center, Tabriz University of Medical Sciences, P.O. Box: 53714161, Tabriz, Iran.
Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran.
Comput Biol Chem. 2021 Feb;90:107416. doi: 10.1016/j.compbiolchem.2020.107416. Epub 2020 Nov 17.
Different bioinformatic methods apply various approaches to predict how much the effect of a SNP could be deleterious and therefore their results may differ significantly. However, variation studies often need to consider an integrated prediction result to analyze the effect of SNPs. To address this problem, we used an algorithm to map ordinal predictions to a numeral space and averaging them, and based on it we developed the ISNPranker web-tool (http://isnpranker.semilab.ir/). It takes heterogonous outputs of different predictors and generates integrated numerical predictions and ranks SNPs based on them. Afterward, we used ISNPranker to identify the most deleterious coding SNPs (cSNPs) of the human aryl hydrocarbon receptor (AHR) gene. AHR is a ligand-activated transcription factor that governs many molecular and cellular mechanisms and cSNPs may affect its structure, interactions, and function. Forty validated cSNPs of AHR were initially analyzed using 16 publicly available SNP analyzers and the results were introduced to the ISNPranker and integrated predictions were obtained. The cSNPs were ranked in 34 levels of danger and rs200257782 in the ARNT dimerization domain (ADD) of AHR was identified as the most deleterious cSNP. The rs148360742, which affect ADD and Hsp90 binding domain (HBD) was in the second rank and the third and fourth ranks were occupied by ADD-located variations rs571123681 and rs141667112 respectively. In conclusion, we introduced ISNPranker, which is a web-tool for integrative ranking of SNPs, and we showed that AHR structure and function may be highly sensitive to the cSNPs in the ARNT dimerization domain.
不同的生物信息学方法应用不同的方法来预测 SNP 的影响有多大可能是有害的，因此它们的结果可能有很大的不同。然而，变异研究通常需要考虑综合预测结果来分析 SNPs 的影响。为了解决这个问题，我们使用一种算法将有序预测映射到数字空间并对其进行平均，基于此我们开发了 ISNPranker 网络工具（http://isnpranker.semilab.ir/）。它接收来自不同预测器的异构输出，并生成基于它们的综合数值预测和 SNP 排名。之后，我们使用 ISNPranker 来识别人类芳香烃受体 (AHR) 基因的最具破坏性编码 SNP (cSNP)。AHR 是一种配体激活的转录因子，它控制着许多分子和细胞机制，而 cSNP 可能会影响其结构、相互作用和功能。最初，使用 16 个公开可用的 SNP 分析器分析了 40 个已验证的 AHR cSNP，并将结果引入 ISNPranker 进行综合预测。cSNP 被分为 34 个危险等级，AHR 的 ARNT 二聚化结构域 (ADD) 中的 rs200257782 被鉴定为最具破坏性的 cSNP。影响 ADD 和 Hsp90 结合结构域 (HBD) 的 rs148360742 排名第二，ADD 所在的 rs571123681 和 rs141667112 分别排名第三和第四。总之，我们介绍了 ISNPranker，这是一种 SNP 综合排名的网络工具，我们表明 AHR 的结构和功能可能对 ARNT 二聚化结构域中的 cSNP 高度敏感。
