MIT chemists synthesize plant-derived molecules that hold potential as pharmaceuticals
Large multi-ring-containing molecules known as oligocyclotryptamines have never been produced in the lab until now.
When an antibiotic fails: MIT scientists are using AI to target “sleeper” bacteria
Most antibiotics target metabolically active bacteria, but with artificial intelligence, researchers can efficiently screen compounds that are lethal to dormant microbes.
Using AI, MIT researchers identify a new class of antibiotic candidates
These compounds can kill methicillin-resistant Staphylococcus aureus (MRSA), a bacterium that causes deadly infections.
Nanoparticle-delivered RNA reduces neuroinflammation in lab tests
MIT researchers find that in mice and human cell cultures, lipid nanoparticles can deliver a potential therapy for inflammation in the brain, a prominent symptom in Alzheimer’s.
Future science at the molecular level
Brad Pentelute and his lab compel the anthrax delivery system to deliver antibody and peptide variants into cells to treat cancer.
Molecule reduces inflammation in Alzheimer’s models
A potential new Alzheimer’s drug represses the harmful inflammatory response of the brain’s immune cells, reducing disease pathology, preserving neurons, and improving cognition in preclinical tests.
How to help high schoolers prepare for the rise of artificial intelligence
A one-week summer program aims to foster a deeper understanding of machine-learning approaches in health among curious young minds.
Learning the language of molecules to predict their properties
This AI system only needs a small amount of data to predict molecular properties, which could speed up drug discovery and material development.
New model offers a way to speed up drug discovery
By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.
Using AI, scientists find a drug that could combat drug-resistant infections
The machine-learning algorithm identified a compound that kills Acinetobacter baumannii, a bacterium that lurks in many hospital settings.
Speeding up drug discovery with diffusion generative models
MIT researchers built DiffDock, a model that may one day be able to find new drugs faster than traditional methods and reduce the potential for adverse side effects.
Angela Koehler takes on the most challenging drug targets
Using biological, chemical, and engineering tools, she has developed strategies to attack molecules once thought to be “undruggable.”
Scientists chart how exercise affects the body
A new study maps the genes and cellular pathways that contribute to exercise-induced weight loss.
Neurodegenerative disease can progress in newly identified patterns
A machine-learning method finds patterns of health decline in ALS, informing future clinical trial designs and mechanism discovery. The technique also extends to Alzheimer’s and Parkinson’s.
Artificial intelligence model finds potential drug molecules a thousand times faster
A geometric deep-learning model is faster and more accurate than state-of-the-art computational models, reducing the chances and costs of drug trial failures.