A promising application of the huge amounts of data from the Human Genome Project currently available offers new opportunities for identifying the genetic predisposition and developing a better understanding of complex diseases such as cancers. The main focus of cancer genetics is the study of mutations that are causally implicated in tumorigenesis. The identification of such causal mutations does not only provide insight into cancer biology but also presents anticancer therapeutic targets and diagnostic markers. In this study, we evaluated the Single Nucleotide Polymorphisms (SNPs) that can alter the expression and the function in MLL gene through computational methods. We applied an evolutionary perspective to screen the SNPs using a sequence homologybased SIFT tool, suggested that 10 non-synonymous SNPs (nsSNPs) (50%) were found to be deleterious. Structure based approach PolyPhen server suggested that 5 nsSNPS (25%) may disrupt protein function and structure. PupaSuite tool predicted the phenotypic effect of SNPs on the structure and function of the affected protein. Structure analysis was carried out with the major mutations that occurred in the native protein coded by MLL gene is at amino acid positions Q1198P and K1203Q. The solvent accessibility results showed that 7 residues changed from exposed state in the native type protein to buried state in Q1198P mutant protein and remained unchanged in the case of K1203Q. From the overall results obtained, nsSNP with id (rs1784246) at the amino acid position Q1198P could be considered as deleterious mutation in the acute leukemia caused by MLL gene.