Single amino acid substitutions within protein structures often manifest with clinical conditions in humans. The mutation of a single amino can significantly alter protein folding and stability, or change protein dynamics to influence function. The chemical engineering field has developed a large toolset for predicting the influence of point mutations with the aim of guiding the design of improved and more stable proteins. Here, we reverse this general protocol and adapt these tools for the prediction of damaging mutations within proteins. Mutations to fumarate hydratase (FH), an enzyme of the citric acid cycle, can lead to human diseases. The inactivation of FH by mutation causes leiomyomas and renal cell carcinoma by subsequent fumarate buildup and reduction in available malate. We present a scheme for accurately predicting the clinical effects of every possible mutation in FH by adaptation to a database of characterized damaging and benign mutations. Using energy prediction tools Rosetta and FoldX coupled with molecular dynamics simulations, we accurately predict individual mutations as well as mutational hotspots with a high disruptive capability in FH. Furthermore, through dynamic analysis, we find that hinge regions of the protein can be stabilized or destabilized by mutations, with mechanistic implications for the functional ability of the enzyme. Finally, we categorize all potential mutations in FH into functional groups, predicting which known mutations in the human population are loss of function, therefore having clinical implications, and validate our findings through metabolomics data of characterized human cell lines.