Protein complexes are fundamental to all biological processes. Public repositories have expanded to include millions of potential protein–protein interactions (PPIs) from human and diverse model organisms. Yet, large-scale structural characterization of these complexes—especially across different biological kingdoms—has lagged far behind, leaving most potential and unidentified interactions unresolved. Here, we present a comprehensive atlas of 1.1 million predicted protein–protein interaction structures generated with the AlphaFold2-based ColabFold framework. This dataset spans proteome-wide interactions from bacteria, archaea, humans, mice, plants, and human–virus pairs. Overall, we identify 181,671 high-confidence protein complex structures, especially 37,855 in the human interactome. Structural clustering revealed numerous conserved protein complex architectures shared across kingdoms, providing insights into previously uncharacterized biological functions. Supported by co-immunoprecipitation experiments, we further identify candidate viral receptors for Human mastadenovirus A and Papiine alphaherpesvirus 2. Comparative analyses integrating our complex structures with the AlphaFold monomeric structure database uncovered widespread gene fusion and fission events during evolution. Finally, we demonstrate how our dataset can enhance protein binding–surface prediction using deep learning approaches, illustrating its broad utility beyond structural modeling alone. Altogether, this atlas to our knowledge, represents one of the most extensive cross-kingdom resources and opens avenues for future discoveries in various biomedical applications. Protein complexes are the machinery of life, yet mapping their structures across different species is challenging. This study presents an atlas of 1.1million cross-kingdom structures, revealing 181,671 high-confidence complexes that uncover new higher-order structures and evolutionary links.
Qi et al. (2026) studied this question.