AI-powered protein structure prediction now extends beyond individual protein structures to modeling protein complexes, ligand interactions, protein-protein docking, and antibody-antigen binding. But different algorithms have different strengths and limitations.
Join us Wednesday, October 21st, 2026 | 11:00 AM CDT for a technical look at the AI-powered structure prediction tools available in Lasergene Protein: Boltz-1 and Boltz-2, ESMFold2, OpenDDE, ColabFold, and ColabDock. Presenters Thomas Leary, Protein Product Specialist, and Erik Edlund, Protein Application Developer, will discuss the pros and cons of each approach and demonstrate their uses with real data.
- Visualize, compare, and evaluate protein structure models
- Interpret prediction confidence metrics and assess model quality
- Analyze sequence variation and its structural impact
- Generate predictions using Boltz and AlphaFold-Multimer
- Leverage new batch prediction workflows to efficiently process larger sets of protein sequences
- Use the new guided protein structure prediction workflow to simplify setup and streamline modeling
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