Efficient and effective searching in protein data presents a unique challenge due to their complex and unsortable nature. Many sequence-based search methods exist, but by definition lack information about 3D spatial arrangements (structures) that are crucial in understanding a protein's function. Addressing this challenge is important in advancing biological research, which relies on identifying similar protein structures, hence their biological functions, which may e.g. lead to better intuition on how different proteins react to different drug treatments. Similarity searching therefore emerges as a practical way of defining and addressing the problem, enabling the comparison of proteins based on their structural characteristics. The creation of AlphaFold 2 and subsequent open-sourcing of the AlphaFold database revolutionized the field of structural biology. With 214M protein structures, AlphaFold DB is the second-largest protein database in the world containing a wealth of information waiting to be scientifically used. However, there is currently no tool enabling structural similarity search in AlphaFold DB. This thesis aims to contribute to the scientific community by implementing a modern web application search engine for similarity searching in protein structures in the AlphaFold Database. In its creation, the student will: 1) study relevant literature and understand proteins, their biological importance, and their digital processing, 2) Analyze similar search applications and propose functional and non-functional requirements 3) Design and implement the application 4) Incorporate third-party software tools such as molecular dynamics graphics for visualization and AlphaFold DB's metadata to the application. Throughout the process, the student will communicate with domain experts from structural biology, gather their feedback, and incorporate it into the application. In adherence to open science principles, the application will be free to use, without the need to register or log in and its code will be open-source. The application will communicate with a similarity searching backend through API. Understanding the application's potential, the application will be considered for submission to a biology-oriented journal.