用计算机分析MARS1基因阐明与间质性肺和肝脏疾病相关的低频变异

Aamna Syed, R. Mateen, Ayman Naeem, Zainab Asif Mirza, Muhammad Usman Ghani, M. Hussain
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摘要

MARS1基因突变与间质性肺和肝脏疾病的发展有关。目前的研究旨在通过硅分析来预测mar1最有害的错义和剪接变异体,这些变异体会破坏蛋氨酸-tRNA合成酶1 (Methionyl-tRNA合成酶1)的功能,催化蛋氨酸与tRNA的连接,对蛋白质的生物合成至关重要。从gnomAD数据库中检索到492个变异,通过CADD进行分析,308个PHRED评分≥20的错义变异进一步通过CAPICE、META-SNP和condel进行分析。通过筛选nssnp检测到85个对蛋白质结构有有害影响的snp。此外,通过DynaMut、DUET、i-Stable2.0和YASARA等不同的工具进行了硅稳定性分析。利用从RCSB PDB (PDB ID: 5GL7)和UCSF Chimera获得的mar1蛋白结构进行可视化。NetSurf-2.0通过残基在结构中的位置获得蛋白质功能分析。我们的研究结果表明,蛋白质的结构发生了明显的破坏,蛋白质的基序和功能发生了改变,我们利用PROSITE数据库预测了翻译后修饰位点和4个具有蛋白质结构改变作用的显著非单核苷酸多态性。剪接分析由SPiCE, Human Splice Finder进行。结果表明,基因可以确定可能的致病变异,为进一步的体外实验研究提供依据。
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In Silico Analysis of MARS1 Gene to Elucidate Low- Frequency Variants Associated with Interstitial Lung and Liver Disease
Mutation in MARS1 gene is linked to the development of Interstitial lung and liver disease. The current study aimed in silico analysis to predict the most harmful missense and spliced variants of MARS1 that damage the functionality of Methionyl-tRNA synthetase 1 (MARS 1), catalyses the ligation of methionine to tRNA and is essential forprotein biosynthesis. A total of 492 variants were retrieved from the gnomAD database and analysed by CADD, 308 missense variants with PHRED score ≥ 20 were further analysed by CAPICE, META-SNP and CONDEL.85 SNPs detected with deleterious impact on protein structure by screening nsSNPs. Moreover, in-silico stability analysis was done by different tools like DynaMut, DUET, i-Stable2.0 and YASARA. MARS1 protein structure obtained from RCSB PDB (PDB ID: 5GL7) and UCSF Chimera was used for its visualisation. NetSurf-2.0 obtained the analysis of protein functioning by position of residue in the structure. Our results showed that the structure of proteins was significantly deleterious and protein motif and function were changed, we proceeded to use the PROSITE database to forecast the posttranslation modification sites and four significant nsSNPs with protein structure change effects. Splice analysis was conducted by SPiCE, Human Splice Finder. It concludes in silico analysis, genes can determine likely pathogenic variation for further in vitro experimental study.
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