IN-SILICO SCREENING AND MODELING OF DELETERIOUS nsSNPs IN HUMAN GENE FBN1 FOR MARFAN SYNDROMEAbstract
Marfan syndrome (MFS) is a common dominant inherited disorder that affects connective tissue, which is associated with mutation of the gene FBN1. The protein encoded by this gene contributes to the final structure of microfibrils. Single nucleotide polymorphisms (SNPs) of this gene links to variations in gene expression phenotypically among patients. Therefore SNPs would be the main target for identification and analysis, which may help in further diagnosis of such life-threatening disorder. In this study, various computational methods have been used to analyze the genetic variations and identify non-synonymous or amino acid-changing SNPs (nsSNP). It can quicken to evaluate a considerable outcome of a mutation before literally doing the lab work. In total, 475 high-risk nsSNPs have been identified using the NCBI SNPs database. Among these nsSNPs, residues are assigned to predict deleterious or disease-related nsSNP. The conservation of functional amino acid residues and secondary and tertiary structure predictions were also reported using various tools. Swiss-Pdb Viewer allows changing amino acid side chains, causing an artificial mutation to the model. Further, HOPE and Chimera software have managed to analyze the changing structures due to the mutation and the visualization of protein 3D structure. The present article points to lay out an overview and a future direction for genetic study of this rare hereditary disorder by in silico analysis.
M. Radha *, S. M. Devi and J. Suganya
Department of Bioinformatics, School of Life Sciences, Vels Institute of Science Technology and Advanced Studies, Chennai, Tamil Nadu, India.
03 April 2020
30 September 2020
05 October 2020
01 April 2021