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New AI tools use plain English to create functional proteins, making biology research easier and opening doors to innovative drug designs.

MIT scientists have released a new open source AI model to predict protein structure with a performance similar to AlphaFold3.

MIT and Harvard researchers develop a new AI method to predict protein locations in cells, aiding disease diagnosis and research.

"Biggest health challenge"

Engineered cells use a glowing amino acid to reveal real-time protein modifications in diseases like cancer.

Researchers design proteins that respond to multiple body signals for targeted treatments, potentially reducing side effects in diseases like cancer.

Researchers use generative AI to create bacteria-killing peptides from scratch, matching approved drugs in tests and offering hope against antibiotic resistance.

A user-friendly AI method generates custom proteins to control biological interactions, making advanced binder discovery accessible without needing vast screening or expert computing skills.

This breakthrough uses a protein from living cells as a qubit to sense tiny changes in biology, potentially revolutionizing how we study cells and advance quantum technology.

Researchers use a new technique to reveal how protein prediction tools make decisions, improving choices for drug and vaccine development while uncovering hidden biological details.