Single nucleotide polymorphisms (SNPs) are gaining importance as they play a significant role in determining susceptibility to disease and prognosis of the treatment. Moreover, understanding the impact of the SNPs on the protein and in turn, its effect on drug response would be a very useful information for personalized medicine. Studying the phenotypic effects of SNPs is a complex and time consuming process. Computational prediction methods have transformed the process and hence in this study, using various computational tools, we present the effects of SNPs of cyp19a1 that encodes the enzyme, aromatase which is involved in the biosynthesis of estrogen. Missense mutations were retrieved from the public database, dbSNP and UniProtKB. The deleterious effects of these mutations on the protein were analyzed using six different computational tools and categorized as pathogenic or neutral. Protein's stability was investigated using I Mutant v3.0 which classified the impact as “destabilizing” or “stabilizing”. Further, mutation analysis was also carried out using the deleterious mutations to understand the effect of substitutions on the protein. Docking simulations of native and mutant C437Y with small molecules such as epigallocatechin gallate, enterolactone and epigallocatechin were also studied in detail that revealed the structural changes in binding and energy differences due to the single amino acid polymorphism. © 2016 Elsevier Inc.