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In-silico predictions of deleterious SNPs in Human ephrin type-A receptor 3 (EPHA3) gene
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Abstract
Ephrin type-A receptor 3 (EPHA3) is a receptor tyrosine kinase encoded by the EPHA3 gene, involves in many biological functions, such as cell migration, adhesion, etc. Overexpression or inactivation of EPHA3 receptors can be complicit in various oncogenic events. Therefore, SNP analysis is required to screen out the deleterious SNPs, such as non-synonymous SNPs (nsSNPs), and in-silico analysis is an effective way to do this screening process. Using eight bioinformatics tools, 81 nsSNPs were found as potential harmful nsSNPs by in-silico analysis among 631 nsSNPs that were retrieved from the dbSNP database. 77 out of 81 substitutions were found as highly conserved by ConSurf analysis. G628E, I652M nsSNPs were found to be present in the ATP-binding site. N751D was found in one of the catalytic residues and P824S in the αF-αG loop in the substrate-binding region. Y596H, Y779C & D598G nsSNPs were found to be associated with activation and regulatory mechanism. R66S, R160H, R104Q nsSNPs were present in the EPH-ligand binding domain that has a higher probability of interfering with ligand-receptor interactions. 21 SNPs associated with the alteration of miRNA target site at 3’ UTR region, which may be responsible for affecting post-transcriptional regulation of EPHA3 gene. These findings will provide necessary data to explore various diseases or cancers pertinent to the EPHA3 receptor protein, will provide remedial biomarkers, may help in molecular diagnosis, and help to design target-specific therapeutic agents.
Springer Science and Business Media LLC
Title: In-silico predictions of deleterious SNPs in Human ephrin type-A receptor 3 (EPHA3) gene
Description:
Abstract
Ephrin type-A receptor 3 (EPHA3) is a receptor tyrosine kinase encoded by the EPHA3 gene, involves in many biological functions, such as cell migration, adhesion, etc.
Overexpression or inactivation of EPHA3 receptors can be complicit in various oncogenic events.
Therefore, SNP analysis is required to screen out the deleterious SNPs, such as non-synonymous SNPs (nsSNPs), and in-silico analysis is an effective way to do this screening process.
Using eight bioinformatics tools, 81 nsSNPs were found as potential harmful nsSNPs by in-silico analysis among 631 nsSNPs that were retrieved from the dbSNP database.
77 out of 81 substitutions were found as highly conserved by ConSurf analysis.
G628E, I652M nsSNPs were found to be present in the ATP-binding site.
N751D was found in one of the catalytic residues and P824S in the αF-αG loop in the substrate-binding region.
Y596H, Y779C & D598G nsSNPs were found to be associated with activation and regulatory mechanism.
R66S, R160H, R104Q nsSNPs were present in the EPH-ligand binding domain that has a higher probability of interfering with ligand-receptor interactions.
21 SNPs associated with the alteration of miRNA target site at 3’ UTR region, which may be responsible for affecting post-transcriptional regulation of EPHA3 gene.
These findings will provide necessary data to explore various diseases or cancers pertinent to the EPHA3 receptor protein, will provide remedial biomarkers, may help in molecular diagnosis, and help to design target-specific therapeutic agents.
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