AI-Driven Computational Modeling for Structural Biology and Protein Engineering

Scope

The symposium welcomes researchers and students working on computational and experimental approaches to biomolecular and protein engineering. Relevant topics include AI and machine learning for protein structure and function; protein–protein and antibody–antigen interactions; protein and enzyme engineering; structure-based prediction and design; geometric and graph neural networks for biomolecular systems; protein language models and multimodal biological models; molecular stability and dynamics; interpretable AI for biomolecular applications; computational screening and candidate prioritization; and integration of AI predictions with experimental engineering workflows. Contributions involving methodological developments, benchmark studies, experimental validation, and applications to therapeutics, enzymes, antibodies, or other engineered biomolecular systems are encouraged.