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Using Generative AI to Design New Therapeutic Proteins with Evozyne

Data in Biotech

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Innovating Protein Engineering Through Evolution

This chapter explores the application of evolutionary principles in the design of therapeutic proteins, emphasizing the significance of ancestral state reconstruction. It discusses the role of machine learning in understanding protein relationships and generating novel biomolecules, while also addressing the challenges in evaluating model efficacy. By focusing on enzymology and utilizing data from metagenomic databases, the chapter highlights a unique iterative approach to protein engineering that distinguishes it from traditional structural design methods.

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