In-Silico pathogenicity prediction of rs۲۱۴۵۲۶۳۶۴۲ in human CEBPA gene in Acute myeloid leukemia (AML)

Acute myeloid leukemia (AML) is the most common leukemia among the adult population and accounts for about ۸۰% of all cases. It is characterized by clonal expansion of immature "blast cells" in the peripheral blood and bone marrow resulting in ineffective erythropoiesis and bone marrow failure. AML is characterized by mutations of the genes involved in hematopoiesis. One of these genes is CEBPA gene. CEBPA encodes the CCAAT/enhancer-binding protein alpha (C/EBPα), a transcription factor that plays a key role in granulocyte development. Consequently, this study was undertaken to find the pathogenic SNPs in CEBPA. Among all SNPs, we have studied on rs۲۱۴۵۲۶۳۶۴۲. In this study we used several bioinformatic tools such as PolyPhen-۲, SIFT and HOPE to predict pathogenicity of this SNP. We found the FASTA sequence of related protein by NCBI. SIFT can predict pathogenicity of SNP by checking the conversion of aminoacids according to the sequence. UniProt shows different SNPs of gene and different variants of protein. We used PolyPhen-۲ to find out if this SNP is damaging or not. Hope predicted the amount of pathogenicity by MetaRNN score. It can range from ۰.۰ to ۱.۰. The higher, the more likely it is to be pathogenic. SWISS-MODEL is a protein structure modeling. The rs۲۱۴۵۲۶۳۶۴۲ affects the protein function with a score of ۰.۰۲ by the SIFT, and was predicted to be possibly damaging with a score of ۰.۸۷۴ by the PolyPhen-۲. This variant’s MetaRNN score is ۰.۵۱۵۳۱۳۶ by the HOPE and it is likely to be pathogenic. There is a difference in charge between the wild-type and mutant amino acid. The charge of the wild-type residue will be lost, this can cause loss of interactions with other molecules or residues. In conclusion, this study suggested that D۷۵N missense variant of CEBPA protein would affect the protein function and can be pathogenic.

کلیدواژه ها:

Acute myeloid leukemia (AML) ، CEBPA gene ، SNP ، rs۲۱۴۵۲۶۳۶۴۲ ، pathogenicity prediction