In silico analysis of CDC73 gene revealing 11 novel SNPs with possible association to Hyperparathyroidism-Jaw Tumor syndrome

AbstractHyperparathyroidism-Jaw Tumor (HPT-JT) is an autosomal dominant disorder with variable expression, with an estimated prevalence of 6.7 per 1,000 population. Genetic testing for predisposing CDC73 (HRPT2) mutations has been an important clinical advance, aimed at early detection and/or treatment to prevent advanced disease. The aim of this study is to assess the most deleterious SNPs mutations on CDC73 gene and to predict their influence on the functional and structural levels using different bioinformatics tools. Method: Computational analysis using twelve different in-silico tools including SIFT, PROVEAN, PolyPhen-2, SNAP2, PhD-SNP, SNPs&GO, P-Mut, I-Mutant ,Project Hope, Chimera, COSMIC and dbSNP Short Genetic Variations were used to identify the impact of mutations in CDC73 gene that might be causing jaw tumor. Results: From (733) SNPs identified in the CDC73 gene we found that only Eleven SNPs (G49C, L63P, L64P, D90H, R222G, W231R, P360S, R441C, R441H, R504S and R504H) has deleterious effect on the function and structure of protein and expected to cause the syndrome. Conclusion: Eleven substantial genetic/molecular aberrations in CDC73 gene identified that could serve as diagnostic markers for hyperparathyroidism-jaw tumor (HPT-JT).

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In silico analysis of CDC73 gene revealing 11 novel SNPs associated with Jaw Tumor Syndrome

10.1101/729764 ◽

2019 ◽

Author(s):

Abdelrahman H. Abdelmoneim ◽

Alaa I. Mohammed ◽

Esraa O. Gadim ◽

Mayada A.Mohammed ◽

Sara H. Hamza ◽

...

Keyword(s):

In Silico ◽

Autosomal Dominant ◽

In Silico Analysis ◽

Autosomal Dominant Disorder ◽

Variable Expression ◽

Back Ground ◽

And Function ◽

Molecular Aberrations ◽

The Impact ◽

Silico Analysis

AbstractBack groundhyperparathyroidism-jaw tumor (HPT-JT) is an autosomal dominant disorder with variable expression, with an estimated prevalence of 6.7 per 1,000 population. Genetic testing for predisposing CDC73 (HRPT2) mutations has been an important clinical advance, aimed at early detection and/or treatment to prevent advanced disease. The aim of this study is to assess the effect of SNPs on CDC73 structure and function using different bioinformatics tools.MethodComputational analysis using eight different in-silico tools including SIFT, PROVEAN, PolyPhen-2, SNAP2, PhD-SNP, SNPs&GO, PMut and Imutant were used to identify the impact on the structure and/or function of CDC73 gene that might be causing jaw tumour.ResultsFrom (733) SNPs identified in the CDC73 gene we found that only Eleven were deleterious to the function and structure of protein and expected to cause syndrome.ConclusionEleven substantial genetic/molecular aberrations in CDC73 gene were identified that could serve as actionable targets for chemotherapeutic intervention in patients whose disease is no longer surgically curable.

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Pediatric Liddle Syndrome Caused by a Novel SCNN1G Variant in a Chinese Family and Characterized by Early-Onset Hypertension

American Journal of Hypertension ◽

10.1093/ajh/hpaa037 ◽

2020 ◽

Vol 33 (7) ◽

pp. 670-675

Author(s):

Peng Fan ◽

Xiao-Cheng Pan ◽

Di Zhang ◽

Kun-Qi Yang ◽

Ying Zhang ◽

...

Keyword(s):

Early Onset ◽

In Silico ◽

Genetic Diagnosis ◽

In Silico Analysis ◽

Missense Variant ◽

Chinese Family ◽

Clinical Genetic ◽

Autosomal Dominant Disorder ◽

Liddle Syndrome ◽

Silico Analysis

Abstract BACKGROUND Liddle syndrome (LS), an autosomal dominant disorder, is a common monogenic hypertension in pediatrics. In this study, we reported a novel SCNN1G variant in a Chinese family with pediatric LS, and conduct a systematic review of epithelial sodium channel (ENaC)-gene-positive LS cases to conclude the clinical genetic features of LS in childhood. METHODS Next-generation sequencing and in silico analysis were performed in the proband to discover candidate variants. Sanger sequencing was used to identify the predicted likely pathogenic variant. LS patients in this family were treated with amiloride. The Medline database was searched to summarize clinical features of pediatric LS cases whose age at genetic diagnosis was not more than 18 years. RESULTS Genetic analysis identified a novel SCNN1G missense variant (c.1874C>T, p.Pro625Leu) in the proband with LS in childhood. In silico analysis revealed this heterozygous variant was highly conserved and deleterious. A total of 38 publications described pediatric LS associated with 25 pathogenic variants in SCNN1B and SCNN1G in 54 children. Despite the phenotypic heterogeneity, early-onset hypertension is the most common feature. All LS patients in this family or the reviewed cases showed significantly improvements in hypertension and hypokalemia after treatment with ENaC inhibitors. CONCLUSIONS This study identified a novel SCNN1G missense variant in a patient with pediatric LS, expanding the genetic spectrum of SCNN1G and demonstrating the PY motif of γ-ENaC as a potential mutant region. Early identification and specific management of LS in children and adolescents are important to prevent the development of hypertensive end-organ disease.

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A Novel Amino Acid Substitution, Fibrinogen Bβp.Pro234Leu, Associated with Hypofibrinogenemia Causing Impairment of Fibrinogen Assembly and Secretion

International Journal of Molecular Sciences ◽

10.3390/ijms21249422 ◽

2020 ◽

Vol 21 (24) ◽

pp. 9422

Author(s):

Takahiro Kaido ◽

Masahiro Yoda ◽

Tomu Kamijo ◽

Shinpei Arai ◽

Chiaki Taira ◽

...

Keyword(s):

Cell Lines ◽

In Silico ◽

Contact Region ◽

Chinese Hamster ◽

In Silico Analysis ◽

Enzyme Linked Immunosorbent Assay ◽

Immunoblotting Analysis ◽

Fibrin Polymerization ◽

The Impact ◽

Silico Analysis

We identified a novel heterozygous variant, Bβp.Pro234Leu (fibrinogen Tokorozawa), which was suspected to be associated with hypofibrinogenemia. Therefore, we analyzed the assembly and secretion of this fibrinogen using Chinese hamster ovary (CHO) cells. To determine the impact on the synthesis and secretion of fibrinogen of the Bβp.P234L and γp.G242E substitutions, we established recombinant variant fibrinogen-producing CHO cell lines. Synthesis and secretion analyses were performed using an enzyme-linked immunosorbent assay (ELISA) and immunoblotting analysis with the established cell lines. In addition, we performed fibrin polymerization using purified plasma fibrinogen and in-silico analysis. Both Bβp.P234L and γp.G242E impaired the secretion and synthesis of fibrinogen. Moreover, immunoblotting analysis elucidated the mobility migration of the Bβγ complex in Bβp.P234L. On the other hand, the fibrin polymerization of fibrinogen Tokorozawa was similar to that of normal fibrinogen. In-silico analysis revealed that the Bβp.P234 residue is located in the contact region between the Bβ and γ chains and contacts γp.G242 residue. The present study demonstrated that the Bβp.P234L substitution resulted in hypofibrinogenemia by decreasing the assembly and secretion of fibrinogen. Therefore, there is a possibility that substitutions in the contact region between the Bβ and γ chains impact the assembly and secretion of fibrinogen.

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

10.1101/519926 ◽

2019 ◽

Author(s):

Mujahed I. Mustafa ◽

Abdelrahman H. Abdelmoneim ◽

Nafisa M. Elfadol ◽

Soada A. osman ◽

Tebyan A. Abdelhameed ◽

...

Keyword(s):

In Silico ◽

In Silico Analysis ◽

Structure And Function ◽

Incomplete Penetrance ◽

Nucleotide Polymorphisms ◽

Hereditary Pancreatitis ◽

Novel Mutations ◽

Autosomal Dominant Disorder ◽

And Function ◽

Silico Analysis

AbstractBackgroundHereditary 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.Materials 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.ResultTwo novel mutations out of 339 nsSNPs that are found be deleterious effect on the PRSS1 structure and function.ConclusionThis 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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In silico analysis of non-synonymous single nucleotide polymorphisms of human DEFB1 gene

Egyptian Journal of Medical Human Genetics ◽

10.1186/s43042-020-00110-3 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Harini Venkata Subbiah ◽

Polani Ramesh Babu ◽

Usha Subbiah

Keyword(s):

Single Nucleotide Polymorphisms ◽

In Silico ◽

In Silico Analysis ◽

Gene Interaction ◽

Nucleotide Polymorphisms ◽

Amino Acid Residues ◽

Single Nucleotide ◽

Project Hope ◽

The Impact ◽

Structure And Functions

Abstract Background Single nucleotide polymorphisms (SNPs) play a significant role in differences in individual’s susceptibility to diseases, and it is imperative to differentiate potentially harmful SNPs from neutral ones. Defensins are small cationic antimicrobial peptides that serve as antimicrobial and immunomodulatory molecules, and SNPs in β-defensin 1 (DEFB1 gene) have been associated with several diseases. In this study, we have determined deleterious SNPs of the DEFB1 gene that can affect the susceptibility to diseases by using different computational methods. Non-synonymous SNPs (nsSNPs) of the DEFB1 gene that have the ability to affect protein structure and functions were determined by several in silico tools—SIFT, PolyPhen v2, PROVEAN, SNAP, PhD-SNP, and SNPs&GO. Then, nsSNPs identified to be potentially deleterious were further analyzed by I-Mutant and ConSurf. Post-translational modifications mediated by nsSNPs were predicted by ModPred, and gene-gene interaction was studied by GeneMANIA. Finally, nsSNPs were submitted to Project HOPE analysis. Results Ten nsSNPs of the DEFB1 gene were found to be potentially deleterious: rs1800968, rs55874920, rs56270143, rs140503947, rs145468425, rs146603349, rs199581284, rs201260899, rs371897938, rs376876621. I-Mutant server showed that nsSNPs rs140503947 and rs146603349 decreased stability of the protein, and ConSurf analysis revealed that SNPs were located in conserved regions. The physiochemical properties of the polymorphic amino acid residues and their effect on structure were determined by Project HOPE. Conclusion This study has determined high-risk deleterious nsSNPs of β-defensin 1 and could increase the knowledge of nsSNPs towards the impact of mutations on structure and functions mediated by β-defensin 1 protein.

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In Silico Analysis of Huntingtin Homologs in Lower Eukaryotes

International Journal of Molecular Sciences ◽

10.3390/ijms22063214 ◽

2021 ◽

Vol 22 (6) ◽

pp. 3214

Author(s):

Valentina Brandi ◽

Fabio Polticelli

Keyword(s):

Autosomal Dominant ◽

In Silico Analysis ◽

Computational Approach ◽

Autosomal Dominant Disorder ◽

C Elegans ◽

Functional Conservation ◽

Lower Eukaryotes ◽

Gene Coding ◽

And Function ◽

Silico Analysis

Huntington’s disease is a rare neurodegenerative and autosomal dominant disorder. HD is caused by a mutation in the gene coding for huntingtin (Htt). The result is the production of a mutant Htt with an abnormally long polyglutamine repeat that leads to pathological Htt aggregates. Although the structure of human Htt has been determined, albeit at low resolution, its functions and how they are performed are largely unknown. Moreover, there is little information on the structure and function of Htt in other organisms. The comparison of Htt homologs can help to understand if there is a functional conservation of domains in the evolution of Htt in eukaryotes. In this work, through a computational approach, Htt homologs from lower eukaryotes have been analysed, identifying ordered domains and modelling their structure. Based on the structural models, a putative function for most of the domains has been predicted. A putative C. elegans Htt-like protein has also been analysed following the same approach. The results obtained support the notion that this protein is a orthologue of human Htt.

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Identification of High risk nsSNPs in Human TP53 Gene Associated with Li–Fraumeni Syndrome: An In Silico Analysis Approach

10.1101/2020.12.04.411835 ◽

2020 ◽

Author(s):

Mujahed I. Mustafa ◽

Naseem S. Murshed ◽

Mazen A. Elbasher ◽

Abdelrafie M. Makhawi

Keyword(s):

High Risk ◽

In Silico ◽

3D Structure ◽

In Silico Analysis ◽

Tp53 Gene ◽

Li Fraumeni Syndrome ◽

Functional Inference ◽

Li Fraumeni ◽

The Impact ◽

Silico Analysis

AbstractBackgroundLi–Fraumeni syndrome (LFS) is a cancer–prone conditions caused by a germline mutation of the TP53 gene on chromosome 17p13.1. It has an autosomal dominant pattern of inheritance with high penetrance.PurposeThe aim of this study is to identify the high-risk pathogenic nsSNPs in PT53 gene that could be involved in the pathogenesis of Li–Fraumeni syndrome.MethodsThe nsSNPs in the human PT53 gene retrieved from NCBI, were analyzed for their functional and structural consequences using various in silico tools to predict the pathogenicity of each SNP. SIFT, Polyphen, PROVEAN, SNAP2, SNPs&Go, PHD-SNP, and P-Mut were chosen to study the functional inference while I-Mutant 3.0, and MUPro tools were used to test the impact of amino acid substitutions on protein stability by calculating ΔΔG value. The effects of the mutations on 3D structure of the PT53 protein were predicted using RaptorX and visualized by UCSF Chimera.ResultsA total of 845 PT53 nsSNPs were analyzed. Out of 7 nsSNPs of PT53 three of them (T118L, C242S, and I251N) were found high-risk pathogenic.ConclusionIn this study, out of 7 predicted high-risk pathogenic nsSNPs, three high-risk pathogenic nsSNPs of PT53 gene were identified, which could be used as diagnostic marker for this gene. The combination of sequence-based and structure-based approaches is highly effective for pointing pathogenic regions.

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