A new model predicts how molecules will dissolve in different solvents
Solubility predictions could make it easier to design and synthesize new drugs, while minimizing the use of more hazardous solvents.
Researchers glimpse the inner workings of protein language models
A new approach can reveal the features AI models use to predict proteins that might make good drug or vaccine targets.
How AI could speed the development of RNA vaccines and other RNA therapies
MIT engineers used a machine-learning model to design nanoparticles that can deliver RNA to cells more efficiently.
Using generative AI, researchers design compounds that can kill drug-resistant bacteria
The team used two different AI approaches to design novel antibiotics, including one that showed promise against MRSA.
3 Questions: How to help students recognize potential bias in their AI datasets
Courses on developing AI models for health care need to focus more on identifying and addressing bias, says Leo Anthony Celi.
New model predicts a chemical reaction’s point of no return
Chemists could use this quick computational method to design more efficient reactions that yield useful compounds, from fuels to pharmaceuticals.
With generative AI, MIT chemists quickly calculate 3D genomic structures
A new approach, which takes minutes rather than days, predicts how a specific DNA sequence will arrange itself in the cell nucleus.
A new computational model can predict antibody structures more accurately
Using this model, researchers may be able to identify antibody drugs that can target a variety of infectious diseases.
AI model can reveal the structures of crystalline materials
By analyzing X-ray crystallography data, the model could help researchers develop new materials for many applications, including batteries and magnets.
A new computational technique could make it easier to engineer useful proteins
MIT researchers plan to search for proteins that could be used to measure electrical activity in the brain.