SS3D: Sequence similarity in 3D for comparison of protein families

Abstract Homologous proteins are often compared by pairwise sequence alignment, and structure superposition if the atomic coordinates are available. Unification of sequence and structure data is an important task in structural biology. Here, we present Sequence Similarity 3D (SS3D), a new method for integrating sequence and structure information for comparison of homologous proteins. SS3D quantifies the spatial similarity of residues within a given radius of homologous through-space contacts. The spatial alignments are scored using native BLOSUM and PAM substitution matrices. This work details the SS3D approach and demonstrates its utility through case studies comparing members of several protein families: GPCR, p53, kelch, SUMO, and SARS coronavirus spike protein. We show that SS3D can more clearly highlight biologically important regions of similarity and dissimilarity compared to pairwise sequence alignments or structure superposition alone. SS3D is written in C++, and is available with a manual and tutorial at https://github.com/0x462e41/SS3D/ .