Epimerase-deficiency galactosemia (EDG) is caused by mutations in the UDP-galactose 4'-epimerase enzyme, encoded by gene GALE. Catalyzing the last reaction in the Leloir pathway, UDP-galactose-4-epimerase catalyzes the interconversion of UDP-galactose and UDP-glucose. This study aimed to use in-depth computational strategies to prioritize the pathogenic missense mutations in GALE protein and investigate the systemic behavior, conformational spaces, atomic motions, and cross-correlation matrix of the GALE protein. We searched four databases (dbSNP, ClinVar, UniProt, and HGMD) and major biological literature databases (PubMed, Science Direct, and Google Scholar), for missense mutations that are associated with EDG patients, our search yielded 190 missense mutations. We applied a systematic computational prediction pipeline, including pathogenicity, stability, biochemical, conservational, protein residue contacts, and structural analysis, to predict the pathogenicity of these mutations. We found three mutations (p.K161N, p.R239W, and p.G302D) with a severe phenotype in patients with EDG that correlated with our computational prediction analysis; thus, they were selected for further structural and simulation analyses to compute the flexibility and stability of the mutant GALE proteins. The three mutants were subjected to molecular dynamics simulation (MDS) with native protein for 200 ns using GROMACS. The MDS demonstrated that these mutations affected the beta-sheets and helical region that are responsible for the catalytic activity; subsequently, affects the stability and flexibility of the mutant proteins along with a decrease and more deviations in compactness when compared to that of a native. Also, three mutations created major variations in the combined atomic motions of the catalytic and C-terminal regions. The network analysis of the residues in the native and three mutant protein structures showed disturbed residue contacts occurred owing to the missense mutations. Our findings help to understand the structural behavior of a protein owing to mutation and are intended to serve as a platform for prioritizing mutations, which could be potential targets for drug discovery and development of targeted therapeutics.