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.
Artificial intelligence system rapidly predicts how two proteins will attach
The machine-learning model could help scientists speed the development of new medicines.
Deep learning helps predict new drug combinations to fight Covid-19
Neural network identifies synergistic drug blends for treating viruses like SARS-CoV-2.
New drug combo shows early potential for treating pancreatic cancer
Researchers find three immunotherapy drugs given together can eliminate pancreatic tumors in mice.
3 Questions: Anna Jagielska on printing artificial axons
How 3D-printed models of neuronal axons could accelerate development of new therapies to treat neurodegenerative disorders.
Using computational tools for molecule discovery
Assistant professor Connor Coley is developing tools that would be able to predict molecular behavior and learn from both successes and mistakes.
Machine learning uncovers potential new TB drugs
Computational method for screening drug compounds can help predict which ones will work best against tuberculosis or other diseases.
A chemist who plays with space
Alison Wendlandt explores how the layout of atoms in molecules, such as sugars and drugs, can affect their nature and our bodies.
MIT conference reveals the power of using artificial intelligence to discover new drugs
Inaugural AI Powered Drug Discovery and Manufacturing Conference drew pharmaceutical companies, government regulators, and pioneering drug researchers.
Whitehead Institute team resolves structure of master growth regulator
New research reveals how mTORC1 docks at lysosomal surface.
Automating molecule design to speed up drug development
Machine-learning model could help chemists make molecules with higher potencies, much more quickly.