Siteomix: a PyMOL plugin for the detection, alignment, and similarity analysis of protein‒ligand binding sites

Abstract

The analysis of structural similarity among protein active sites is fundamental to understanding functional relationships between proteins and plays a critical role in structure-based drug design. Detailed characterization of protein‒ligand binding site similarity requires not only fast and accurate computational workflows but also effective platforms for visualizing aligned binding sites and interpreting similarity relationships at the molecular level. Here, we present Siteomix, an integrated plugin for the PyMOL molecular graphics system that automates the detection of binding pockets via the LIGSITE algorithm, visualizes them as discrete point clouds colored by cavity depth, and performs a two-step alignment combining the rigid iterative closest point (ICP) algorithm with differential evolution optimization. The plugin quantifies binding site similarity through three complementary metrics: normalized volumetric overlap (equivalent to the Tanimoto coefficient), the mean nearest neighbor distance after ICP alignment, and root-mean-square deviation after refined alignment, enabling researchers to distinguish global shape complementarity from local geometric congruence. By embedding the entire comparison pipeline within an interactive three-dimensional PyMOL environment, Siteomix facilitates visual assessment of aligned binding sites and supports structure-based drug discovery applications. The plugin is implemented in Python, works on all major operating systems (Windows, macOS, Linux), and is freely available with its source code at https://github.com/KiraVelieva-CH/Siteomix-Plugin.