Article: Harnessing Generative AI to Decode Enzyme Catalysis and Evolution for Enhanced Engineering.
bioRxiv : the preprint server for biology
2023
Abstract: Enzymes, as paramount protein catalysts, occupy a central role in fostering remarkable progress across numerous fields. However, the intricacy of sequence-function relationships continues to obscure our grasp of enzyme behaviors and curtails our ... ...
Abstract | Enzymes, as paramount protein catalysts, occupy a central role in fostering remarkable progress across numerous fields. However, the intricacy of sequence-function relationships continues to obscure our grasp of enzyme behaviors and curtails our capabilities in rational enzyme engineering. Generative artificial intelligence (AI), known for its proficiency in handling intricate data distributions, holds the potential to offer novel perspectives in enzyme research. By applying generative models, we could discern elusive patterns within the vast sequence space and uncover new functional enzyme sequences. This review highlights the recent advancements in employing generative AI for enzyme sequence analysis. We delve into the impact of generative AI in predicting mutation effects on enzyme fitness, activity, and stability, rationalizing the laboratory evolution of |
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Language | English |
Publishing date | 2023-10-12 |
Publishing country | United States |
Document type | Preprint |
DOI | 10.1101/2023.10.10.561808 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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