Biology subjects

Mustafa, M. I.

Publications and source records attributed to Mustafa, M. I..

25 records · Page 2Linked to original sources

bioRxiv2019

In silico analysis of IDH3A gene revealed Novel mutations associated with Retinitis Pigmentosa

BackgroundRetinitis Pigmentosa (RP) refers to a group of inherited disorders characterized by the death of photoreceptor cells leading to blindness. The aim of this study is to identify the pathogenic SNPs in the IDH3A gene and their effect on the structure and function of the protein. Methodwe used different bioinformatics tools to predict the effect of each SNP on the structure and function of the protein. Result20 deleterious SNPs out of 178 were found to have a damaging effect on the protein structure and function. Conclusionthis is the first in silico analysis of IDH3A gene and 20 novel mutations were found using different bioinformatics tools, and they could be used as diagnostic markers for Retinitis Pigmentosa.

bioinformatics↗

bioRxiv2019

In Silico Analysis and Modeling of Novel Pathogenic Single Nucleotide Polymorphisms (SNPs) in Human CD40LG Gene

AbstractO_ST_ABSBackgroundC_ST_ABSThe X-linked hyper-immunoglobulin M syndrome (XHIGM) is a rare, inherited immune deficiency disorder. It is more common in males. Characterized by elevated serum IgM levels and low to undetectable levels of serum IgG, IgA and IgE. Hyper-IgM syndrome is caused by mutations in the CD40LG gene. Located in human Xq26. CD40LG acts as an immune modulator in activated T cells. MethodWe used different bioinformatics tools to predict the effect of each SNP on the structure and function of the protein. Result8 novel SNPs out of 233 were found to have most deleterious effect on the protein structure and function. While modeling of nsSNPs was studied by Project HOPE software. ConclusionBetter understanding of Hyper-IgM syndrome caused by mutations in CD40LG gene was achieved using in silico analysis. This is the first in silico functional analysis of CD40LG gene and 8 novel mutations were found using different bioinformatics tools, and they could be used as diagnostic markers for hyper-IgM syndrome. These 8 novel SNPs may be important candidates for the cause of different types of human diseases by CD40LG gene.

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bioRxiv2019

In Silico Genetics: Identification of pathogenic nsSNPs in human STAT3 gene associated with Job's syndrome

BackgroundAutosomal dominant hyper-IgE syndrome (AD-HIES) or Jobs syndrome is a rare immunodeficiesncy disease that classically presents in early childhood, characterized by eczematoid dermatitis, characteristic facies, pneumatoceles, hyperextensibility of joints, multiple bone fractures, scoliosis, atopic dermatitis and elevated levels of serum IgE (>2000 IU/ml). The term Autosomal dominant hyper-IgE syndrome has primarily been associated with mutations in STAT3 gene, Located in human chromosome 17q21. MethodsThe human STAT3 gene was investigated in dbSNP/NCBI, 962 SNPs were Homo sapiens; of which 255 were missense SNPs. This selected for in silico analysis by multiple in silico tools to investigate the effect of SNPs on STAT3 proteins structure and function. ResultEleven novel mutations out of 255 nsSNPs that are found to be deleterious effect on the STAT3 structure and function. ConclusionA total of eleven novel nsSNPs were predicted to be responsible for the structural and functional modifications of STAT3 protein. The newly recognized genetic cause of the hyper-IgE syndrome affects complex, compartmentalized somatic and immune regulation. This study will opens new doors to facilitate the development of novel diagnostic markers for associated diseases.

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bioRxiv2019

Unmasking of novel mutations within XK gene that could be used as Diagnostic Markers to Predict McLeod syndrome: Using in silico analysis

BackgroundMcLeod neuroacanthocytosis syndrome is a rare X-linked recessive multisystem disorder affecting the peripheral and central nervous systems, red blood cells, and internal organs. MethodsWe carried out in silico analysis of structural effect of each SNP using different bioinformatics tools to predict substitution influence on protein structural and functional level. Result2 novel mutations out of 104 nsSNPs that are found to be deleterious effect on the XK structure and function. ConclusionThe present study provided a novel insight into the understanding of McLeod syndrome, SNPs occurring in coding and non-coding regions, may lead to RNA alterations and should be systematically verified. Functional studies can gain from a preliminary multi-step approach, such as the one proposed here; we prioritize SNPs for further genetic mapping studies. This will be a valuable resource for neurologists, hematologists, and clinical geneticists on this rare and debilitating disease.

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bioRxiv2019

Novel mutations within PRSS1 Gene that could potentially cause hereditary pancreatitis: Using Comprehensive in silico Approach

BackgroundHereditary pancreatitis (HP) is an autosomal dominant disorder with incomplete penetrance characterized by recurring episodes of severe abdominal pain often presenting in childhood. The comprehensive in silico analysis of coding SNPs, and their functional impacts on protein level, still remains unknown. In this study, we aimed to identify the pathogenic SNPs in PRSS1 gene by computational analysis approach.\n\nMaterials and MethodsWe carried out in silico analysis of structural effect of each SNP using different bioinformatics tools to predict Single-nucleotide polymorphisms influence on protein structure and function.\n\nResultTwo novel mutations out of 339 nsSNPs that are found be deleterious effect on the PRSS1 structure and function.\n\nConclusionThis is the first in silico analysis in PRSS1 gene, which will be a valuable resource for future targeted mechanistic and population-based studies.

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bioRxiv2018

Comprehensive in silico Analysis of IKBKAP gene that could potentially cause Familial dysautonomia

BackgroundFamilial dysautonomia (FD) is a rare neurodevelopmental genetic disorder within the larger classification of hereditary sensory and autonomic neuropathies. We aimed to identify the pathogenic SNPs in IKBKAP gene by computational analysis softwares, and to determine the structure, function and regulation of their respective proteins.\n\nMaterials and MethodsWe carried out in silico analysis of structural effect of each SNP using different bioinformatics tools to predict SNPs influence on protein structure and function.\n\nResult41 novel mutations out of 973 nsSNPs that are found be deleterious effect on the IKBKAP structure and function.\n\nConclusionThis is the first in silico analysis in IKBKAP gene to prioritize SNPs for further genetic studies.

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bioRxiv2018

Novel deleterious nsSNPs within MEFV gene that could be used as Diagnostic Markers to Predict Hereditary Familial Mediterranean Fever: Using bioinformatics analysis

BackgroundFamilial Mediterranean Fever (FMF) is the most common auto inflammatory disease (AID) affecting mainly the ethnic groups originating from Mediterranean basin, we aimed to identify the pathogenic SNPs in MEFV by computational analysis software.\n\nMethodsWe carried out in silico prediction of structural effect of each SNP using different bioinformatics tools to predict substitution influence on protein structure and function.\n\nResult23 novel mutations out of 857 nsSNPs that are found to be deleterious effect on the MEFV structure and function.\n\nConclusionThis is the first in silico analysis in 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.

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