Comparing macromolecular complexes - a fully automated benchmarking suite

Protein structure prediction has a long history of benchmarking such as CASP, CAMEO and CAPRI. With the rise of AI-based methods for prediction of macromolecular complexes, benchmarking with large datasets and robust, automated scores to compare predictions against a reference has become essential. Also, the increasing size and complexity of experimentally determined reference structures by crystallography or cryo EM poses challenges for structure comparison methods. In this manuscript, we review the current state of the art in scoring methodologies, identify existing limitations, and present novel approaches for automated scoring of tertiary and quaternary structures, protein-protein interfaces, and protein-ligand complexes. Our methods are designed to scale efficiently, enabling the assessment of large, complex systems. All developments are available in the structure benchmarking framework of OpenStructure. OpenStructure is open source software and available for free at https://openstructure.org/.