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      Genetic Epidemiology of Glucose-6-Dehydrogenase Deficiency in the Arab World

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          Abstract

          A systematic search was implemented using four literature databases (PubMed, Embase, Science Direct and Web of Science) to capture all the causative mutations of Glucose-6-phosphate dehydrogenase (G6PD) deficiency (G6PDD) in the 22 Arab countries. Our search yielded 43 studies that captured 33 mutations (23 missense, one silent, two deletions, and seven intronic mutations), in 3,430 Arab patients with G6PDD. The 23 missense mutations were then subjected to phenotypic classification using in silico prediction tools, which were compared to the WHO pathogenicity scale as a reference. These in silico tools were tested for their predicting efficiency using rigorous statistical analyses. Of the 23 missense mutations, p.S188F, p.I48T, p.N126D, and p.V68M, were identified as the most common mutations among Arab populations, but were not unique to the Arab world, interestingly, our search strategy found four other mutations (p.N135T, p.S179N, p.R246L, and p.Q307P) that are unique to Arabs. These mutations were exposed to structural analysis and molecular dynamics simulation analysis (MDSA), which predicting these mutant forms as potentially affect the enzyme function. The combination of the MDSA, structural analysis, and in silico predictions and statistical tools we used will provide a platform for future prediction accuracy for the pathogenicity of genetic mutations.

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          Most cited references29

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          Human non-synonymous SNPs: server and survey.

          Human single nucleotide polymorphisms (SNPs) represent the most frequent type of human population DNA variation. One of the main goals of SNP research is to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases. Non-synonymous coding SNPs (nsSNPs) comprise a group of SNPs that, together with SNPs in regulatory regions, are believed to have the highest impact on phenotype. Here we present a World Wide Web server to predict the effect of an nsSNP on protein structure and function. The prediction method enabled analysis of the publicly available SNP database HGVbase, which gave rise to a dataset of nsSNPs with predicted functionality. The dataset was further used to compare the effect of various structural and functional characteristics of amino acid substitutions responsible for phenotypic display of nsSNPs. We also studied the dependence of selective pressure on the structural and functional properties of proteins. We found that in our dataset the selection pressure against deleterious SNPs depends on the molecular function of the protein, although it is insensitive to several other protein features considered. The strongest selective pressure was detected for proteins involved in transcription regulation.
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            ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information.

            We recently developed algorithmic tools for the identification of functionally important regions in proteins of known three dimensional structure by estimating the degree of conservation of the amino-acid sites among their close sequence homologues. Projecting the conservation grades onto the molecular surface of these proteins reveals patches of highly conserved (or occasionally highly variable) residues that are often of important biological function. We present a new web server, ConSurf, which automates these algorithmic tools. ConSurf may be used for high-throughput characterization of functional regions in proteins. The ConSurf web server is available at:http://consurf.tau.ac.il. A set of examples is available at http://consurf.tau.ac.il under 'GALLERY'.
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              SNPs, protein structure, and disease.

              Inherited disease susceptibility in humans is most commonly associated with single nucleotide polymorphisms (SNPs). The mechanisms by which this occurs are still poorly understood. We have analyzed the effect of a set of disease-causing missense mutations arising from SNPs, and a set of newly determined SNPs from the general population. Results of in vitro mutagenesis studies, together with the protein structural context of each mutation, are used to develop a model for assigning a mechanism of action of each mutation at the protein level. Ninety percent of the known disease-causing missense mutations examined fit this model, with the vast majority affecting protein stability, through a variety of energy related factors. In sharp contrast, over 70% of the population set are found to be neutral. The remaining 30% are potentially involved in polygenic disease. Copyright 2001 Wiley-Liss, Inc.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                17 November 2016
                2016
                : 6
                Affiliations
                [1 ]Department of Integrative Biology, School of Biosciences and Technology, VIT University, Vellore , India
                [2 ]College of Health Sciences, Biomedical Sciences Department, Qatar University , Doha, Qatar
                [3 ]CIBER Pathophysiology of obesity and nutrition CB06/03, Carlos III Health Institute. Unidad de Gestion Clínica Intercentros de Endocrinología y Nutrición, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Regional Universitario de Málaga/Universidad de Málaga , 29009, Málaga, Spain
                Author notes
                Article
                srep37284
                10.1038/srep37284
                5112515
                27853304
                13a641e4-6d93-423d-a346-d7ec22e6d04b
                Copyright © 2016, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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