Protein similarity and evolutionary relationships are traditionally assessed using sequence alignment metrics. However, structural conservation often persists even when sequence similarity is minimal, particularly in the case of viral proteins. This chapter presents an innovative pipeline for protein comparison and analysis, inspired by methodologies from astrophysics and cosmology. By transforming protein shapes into spherical models, our approach enables a novel comparison based on structure rather than sequence. We tested this method using a dataset of low-sequence identity viral proteins and demonstrated that it outperforms conventional sequence-based techniques. The potential for this technology to advance protein analysis is substantial, especially for proteins with highly divergent sequences but conserved structures.