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Advances in Bioinformatics
Volume 2019, Article ID 1651587, 13 pages
https://doi.org/10.1155/2019/1651587
Research Article

Novel Deleterious nsSNPs within MEFV Gene that Could Be Used as Diagnostic Markers to Predict Hereditary Familial Mediterranean Fever: Using Bioinformatics Analysis

1Department of Biochemistry, University of Bahri, Sudan
2Department of Biotechnology, Africa City of Technology, Sudan

Correspondence should be addressed to Mujahed I. Mustafa; moc.liamg@44miharbidehajum

Received 29 September 2018; Revised 2 January 2019; Accepted 21 January 2019; Published 4 June 2019

Academic Editor: Nurit Haspel

Copyright © 2019 Mujahed I. Mustafa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background. Familial Mediterranean Fever (FMF) is the most common autoinflammatory disease (AID) affecting mainly the ethnic groups originating from Mediterranean basin. We aimed to identify the pathogenic SNPs in MEFV by computational analysis software. Methods. We carried out in silico prediction of structural effect of each SNP using different bioinformatics tools to predict substitution influence on protein structure and function. Result. 23 novel mutations out of 857 nsSNPs are found to have deleterious effect on the MEFV structure and function. Conclusion. This is the first in silico analysis of MEFV gene to prioritize SNPs for further genetic mapping studies. After using multiple bioinformatics tools to compare and rely on the results predicted, we found 23 novel mutations that may cause FMF disease and it could be used as diagnostic markers for Mediterranean basin populations.