AI model deciphers the code in proteins that tells them where to go
Whitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.
Whitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.
MIT researchers plan to search for proteins that could be used to measure electrical activity in the brain.
MIT researchers develop “FrameDiff,” a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving gene therapy.
By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.
These tunable proteins could be used to create new materials with specific mechanical properties, like toughness or flexibility.
With further development, the programmable system could be used in a range of applications including gene and cancer therapies.