The chapter explores the developments in training models for complex biomolecules, such as the rosetta fold all atom model, and the shift towards generative models influenced by diffusion and flow matching. It discusses the application of AI in protein engineering for designing new proteins, binders for specific targets like cancer cells, and optimizing binding affinity. The chapter also delves into the challenges and computational aspects of utilizing AI tools like RF diffusion and alpha fold for accelerating the process of protein design and drug discovery.

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