In Silico identification of AML-associated polymorphisms in human CEBPA gene and assessment of anticancer properties of organometallic compounds against Leukemia

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