In Silico Analysis of MARS1 Gene to Elucidate Low- Frequency Variants Associated with Interstitial Lung and Liver Disease

Aamna Syed, Rana Muhammad Mateen Ayman Naeem, Zainab Asif Mirza, Muhammad Usman Ghani, Mureed Hussain*

  • Aamna Syed Department of Life Sciences, School of Science, University of Management and Technology, Lahore
  • Rana Muhammad Mateen Department of Life Sciences, School of Science, University of Management and Technology, Lahore
  • Ayman Naeem Department of Life Sciences, School of Science, University of Management and Technology, Lahore
  • Zainab Asif Mirza Department of Life Sciences, School of Science, University of Management and Technology, Lahore
  • Muhammad Usman Ghani Center of Applied Molecular Biology, University of the Punjab, Lahore
  • Mureed Hussain Department of Life Sciences, School of Science, University of Management and Technology, Lahore
Keywords: Interstitial, Methionyl-tRNA synthetase, loss of mutation, gnomAD, Mutation prediction

Abstract

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.

Published
2023-03-08