Systematic Validation of AlphaFold-Predicted Interactomes with LUCIA

Abstract

Mapping protein-protein interactions (PPIs) at structural resolution is essential for understanding cellular machinery. While tools like AlphaFold enable proteome-wide structural predictions, the field lacks high-throughput experimental methods to verify these predictions at scale and establish empirical thresholds for confidence metrics, such as the widely used interface predicted Template Modeling (ipTM) score. We developed LUCIA (LUminescent Cell-free Interaction Assay), a rapid biochemical screening platform bypassing traditional cloning and protein expression to validate direct binary interactions within days. Applying this to herpesviruses, clinically relevant human pathogens with large proteomes, we generated an exhaustive computational interactome of 23,215 AlphaFold-predicted dimer models across three species (HSV-1, HCMV, and KSHV), accessible via our HerpesPPIs database. Using the HSV-1 interactome as a benchmark, testing 83 high-confidence predicted dimers with LUCIA yielded 23 novel, experimentally validated interactions. By calibrating AlphaFold metrics against this direct binding data, we demonstrated that an ipTM score [≥] 0.80 identifies bona fide interactions with a positive predictive value of 77%. To demonstrate the functional power of this pipeline, we characterized a previously unknown interaction between HSV-1 UL42 and UL8, linking the viral DNA polymerase and helicase-primase complexes. Structure-guided mutations at the predicted and LUCIA-verified UL42-UL8 interface strongly reduced binding in vitro and completely abolished viral replication in cell culture. Combining the scalable LUCIA platform with computational predictions enables researchers to rapidly translate atomic-level models into validated biological mechanisms without the need to solve experimental structures.