Protein Engineering and Computational Analysis of Enzymes to Predict Cancer Mutations

Abstract

Cancer is a dangerous disease that can manifest in multiple forms and areas within the body. Due to its multifaceted nature and tenacity, cancer prevention and treatment methods remain challenging. However, developing methods are ongoing that may help with fighting cancer by engaging in preventing growth at early stages. Protein engineering and enzyme design is a promising field that allows proteins to be strategically edited and designed to target cancers more efficiently. Computational methods allow us to obtain a better understanding of how these proteins can be engineered to fight a disease like cancer. Computational software offers data on protein alignments over multiple species, theoretical protein structures, and predicting co-evolving enzyme pairs, as well as making inferences on how mutations affect residues. Here, I aimed to examine computational protein engineering by exploring predictive software that is publicly accessible, to gain insight into their abilities and draw conclusions on the relation between cancer malignancies and the computational results. Overall, computational analysis and understanding enzyme design can have exciting implications for the world of medicine and allow for robust means of treating diseases like cancer.