The article discusses the significant impact of artificial intelligence, particularly protein language models (PLMs), on protein design and function prediction within synthetic biology. Dr. Etienne Goffient emphasizes the importance of analyzing protein sequences bidirectionally and conditioning models on additional properties for improved predictive accuracy. Applications include optimizing antibodies, refining enzymes, and designing vaccines. With high-quality open-source models like ESM2 and ProGen and expansive datasets like UniProt, the field is advancing rapidly, transforming how we approach biological functions and therapeutic applications.
The interplay between artificial intelligence and synthetic biology has revolutionized our understanding of protein design and function prediction, highlighting the transformative potential of protein language models.
Proteins, often called the building blocks of life, are pivotal to biological functions, and understanding their sequences is essential for predicting their 3D structures.
#artificial-intelligence #synthetic-biology #protein-language-models #protein-design #bioinformatics
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