Susan Schlimpert

AlphaBridge: tools for the analysis of predicted macromolecular complexes • AlphaBridge introduces tools to analyze and visualize the interfaces between predicted macromolecular complexes using data from AlphaFold3. It processes the predicted interactions into intuitive diagrams and 3D models for easy interpretation. • The tool uses a novel “Predicted Merged Confidence” (PMC) matrix, which combines the Predicted Local Distance Difference Test (pLDDT) and Predicted Aligned Error (PAE) metrics to identify multi-component structural modules and binary interfaces with high confidence. • AlphaBridge uses graph-based community clustering to detect interaction motifs in biomolecular complexes, then visualizes these interactions as chord diagrams (“AlphaBridge diagrams”) to provide a clear and intuitive summary of predicted binding interfaces. • The tool allows researchers to evaluate the reliability of interactions in predicted protein-protein, protein-DNA, and protein-RNA complexes, offering a scoring and ranking system for predicted interfaces before detailed analysis. • By varying the cut-off for contact predictions, AlphaBridge can help distinguish between reliable and unreliable predictions, providing insights into physiological relevance. It was particularly useful for evaluating interactions in DNA mismatch repair proteins and RNA binding proteins. • The AlphaBridge webserver (alpha-bridge.eu) offers an interactive platform where users can upload AlphaFold3 prediction files, visualize the predicted 3D structures, and analyze contact interfaces through an integrated web viewer. • AlphaBridge enhances accessibility for both expert and non-expert users by combining multiple layers of information—contact links, prediction confidence, and visual representations—into one interactive diagram, simplifying the evaluation of complex predictions. @TassosPerrakis @rborza_ 💻Code: github.com/PDB-REDO/AlphaBri… 📜Paper: biorxiv.org/content/10.1101/…