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Finding an effective method of delivering drugs to their targets at appropriate amounts has been one of the major objectives in biomedicine. In nature, one successful example of such delivery system exists called “protein cage”. Protein cages are closed structures, which may contain something inside, made up of protein building blocks interacting together. These structures are for example used by viruses to protect and to deliver their genetic information to cells. In practice, altered viral protein cages, called virus-like particles, have already been used in medicine but they still face some challenges in their application. Alternatively, artificial symmetric proteins that can form complex structure without assistance may act as better building blocks for protein cages. Designing artificial symmetric proteins computationally is one of the research interests in the host lab. There have been several artificial symmetric proteins created however, the best strategy to allow these proteins to interact and form protein cages is still yet to be found. This thesis aims to explore one strategy by which portions of the protein are replaced by coiled-like structures called α-helices that can interact together. For this new design of artificial protein to be realized, computational and AI tools were employed. The selected final designs were produced using E. coli bacteria and all of them were structurally determined using CD spectroscopy technique. With this technique, two of the proteins were found to have possible α-helical structures. However, optimization is required in order for the structures of these artificial proteins to be more accurately determined with technique such as X-ray crystallography. Nevertheless, the thesis demonstrates the possibility of the α-helical grafting to the protein with the method applied.