Abstract:
Single Nucleotide Polymorphisms (SNPs) are found to be associated with cancer, especially Acute
Myeloid Leukemia (AML). Functional and structural polymorphism identification is more
important to study and discover therapeutics targets and potential malfunctioning. Different
computational tools were considered to find out disease associated nsSNPs, that may have key role
in structure and function of CEBPA, making them extremely important. Insilico tools which were used in this study are SIFT, PROVEAN, PolPhen-2, SNP&GO, PhD-SNP, ConSurf and I-Mutant. Protein 3D modelling was carried out using RaptorX and MODELLER v9.22, while GeneMANIA and String were used for gene-gene and protein-protein interactions. From our study we found that
L345P, R333C, R339Q, V328G, R327W, L317Q, N292S, E284A, R156W, Y108N and F82Lmutations were the most crucial SNPs. Additionally, the gene-gene interactions showed genes
having correlation with CEBPA co-expressions and importance in several pathways. In future, these 11 mutations should be investigated while studying diseases related to CEBPA, especially for AML. Being the first of its type, future perspectives are proposed in this study, which will help in precision medicine. Animal models would be of great significance in finding out CEBPA effects in diseases
