Unmasking of two mutations within XK gene that could be used as diagnostic markers to predict McLeod Syndrome: using in silico analysis

Multidisciplinary Science Journal(2022)

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Abstract
McLeod neuroacanthocytosis syndrome (MSL) is a rare X-linked recessive multisystem disorder affecting the peripheral and central nervous systems, red blood cells, and internal organs. The objective of this study was to identify the most deleterious SNPs within XK gene and to predict their influence on the functional and structural level by a several in silico analysis tools. The raw data of XK gene were recovered from dbSNP database and then used to investigate the damaging effect using SIFT, PolyPhen-2, PROVEAN, SNAP2, SNPs&GO, and PHD-SNP. Furthermore; we submitted the common six damaging results from the previous functional analysis tools to I-mutant 3.0, and MUPro respectively to study their effect on structural perspective. The 3D structure of XK was predicted by RaptorX and visualized using UCSF Chimera to compare the differences between the native and the mutant amino acids. The functional analysis predicted that two SNPs “rs28933690 and rs145996031” have a deleterious effect at functional level. The structural analysis revealed that, the same two mutations predicted a dramatic decrease of the protein stability, thus proposing that the C294R and Y370D mutations within XK could destabilize the amino acid interactions, causing functional abnormalities of XK protein. In this study, the impact of functional mutations in the XK gene was investigated through different computational analysis tool, which determined that (C294R & Y370D) are deleterious SNPs that are a potential responsibility for the functional and structural alterations of XK protein.
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Key words
mcleod syndrome,xk gene,mutations,diagnostic markers
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