Pathogenic predictions of non-synonymous variants and their impacts: A computational assessment of ARHGEF6 gene

Khimsuriya, Yashvant; Chauhan, Jenabhai B.

doi:10.1016/j.ejmhg.2018.05.002

Cited by 3 publications

(3 citation statements)

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“…The SNPs in the coding region of human genes were associated with genetic disorders [ 14 ]. A large number of SNPs have been reported in the database, and it is difficult to screen all the SNPs for the particular phenotype [ 40 , 41 ]. The computational analysis tools help to narrow down and examine the pathogenic SNPs for the specific genetic disorders and in minimizing the risk [ 41 , 42 ].…”

Section: Discussionmentioning

confidence: 99%

“…In the present study, various computational tools based on different algorithms were utilized to screen the most pathogenic nsSNPs of the human SOS1 gene to induce NS. A similar approach has been carried out to test the functional nsSNPs of ARHGEF6, BRAF, TAGAP , and UTY gene [ 41 - 44 ].…”

Section: Discussionmentioning

confidence: 99%

“…The 3D models were generated using I-TASSER for the wild type and mutant SOS1 proteins, and their structural variations were analysed. Similar computational structural analysis have been carried out for various protein’s models like ARHGEF6, BRAF, TAGAP, and UTY [ 41 - 44 ]. Besides, the HOPE tool was utilized to study the amino acid changes between the wild type and mutants.…”

Section: Discussionmentioning

confidence: 99%

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In-Silico and In-Vitro Analysis of Human SOS1 Protein Causing Noonan Syndrome - A Novel Approach to Explore the Molecular Pathways

Sigamani

Rajasingh

Gurusamy

et al. 2021

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Aims: Noonan syndrome (NS) is an autosomal dominant genetic disorder caused by single nucleotide mutation in PTPN11, SOS1, RAF1, and KRAS genes. Background: We hypothesize that in-silico analysis of human SOS1 mutations would be a promising predictor in identifying the pathogenic effect of NS. Methods: Here, we computationally analyzed the SOS1 gene to identify the pathogenic non-synonymous single nucleotide polymorphisms (nsSNPs) to cause NS. The variant information of SOS1 was collected from the SNP database (dbSNP). The variants were further analyzed by in-silico tools I-Mutant, iPTREE-STAB, and MutPred to elucidate their structural and functional characteristics. Results: We found that 11 nsSNPs of SOS1 were more pathogenic to cause NS. The 3D modeling of the wild-type and the 11 nsSNPs were performed using I-TASSER and validated via ERRAT and RAMPAGE. SOS1 interacting proteins were analysed through STRING, which showed that SOS1 interacted with cardiac proteins GATA4, TNNT2, and ACTN2. During these interactions, GRB2 and HRAS act as an intermediate molecules between SOS1 and cardiac proteins. These in-silico analyses were validated using induced cardiomyocytes (iCMCs) derived from NS patients carrying SOS1 gene variant c.1654A>G (NS-iCMCs) and compared with control human skin fibroblast-derived iCMCs (C-iCMCs). Our in vitro data further confirmed that the SOS1, GRB2 and HRAS gene expressions as well as the activated ERK protein, were significantly decreased in NS-iCMCs compared to C-iCMCs. Conclusion: This is the first in-silico and in vitro study demonstrating that 11 nsSNPs of SOS1 were playing a deleterious pathogenic role in causing NS.

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