Every year, global health experts are faced with a high-stakes decision: which flu strains should go into the next seasonal vaccine? The choice must be made months in advance, long before flu season even begins, and it can often feel like a race against the clock. If the selected strains match those that circulate, the vaccine will likely be highly effective. But if the prediction is off, protection can drop significantly, leading to (potentially preventable) illness and strain on healthcare systems.
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Within the past few years, models that can predict the structure or function of proteins have been widely used for a variety of biological applications, such as identifying drug targets and designing new therapeutic antibodies.
In 1954, the world’s first successful organ transplant took place at Brigham and Women’s Hospital, in the form of a kidney donated from one twin to the other. At the time, a group of doctors and scientists had correctly theorized that the recipient’s antibodies were unlikely to reject an organ from an identical twin. One Nobel Prize and a few decades later, advancements in immune-suppressing drugs increased the viability of and demand for organ transplants. Today, over 1 million organ transplants have been performed in the United States, more than any other country in the world.
Understanding how molecules interact is central to biology: from decoding how living organisms function to uncovering disease mechanisms and developing life-saving drugs. In recent years, models like AlphaFold changed our ability to predict the 3D structure of proteins, offering crucial insights into molecular shape and interaction. But while AlphaFold could show how molecules fit together, it couldn’t measure how strongly they bind — a key factor in understanding all aforementioned. That missing piece is where MIT’s new AI model, Boltz-2, comes in.
Programmers can now use large language models (LLMs) to generate computer code more quickly. However, this only makes programmers’ lives easier if that code follows the rules of the programming language and doesn’t cause a computer to crash.
When visual information enters the brain, it travels through two pathways that process different aspects of the input. For decades, scientists have hypothesized that one of these pathways, the ventral visual stream, is responsible for recognizing objects, and that it might have been optimized by evolution to do just that.
The process of discovering molecules that have the properties needed to create new medicines and materials is cumbersome and expensive, consuming vast computational resources and months of human labor to narrow down the enormous space of potential candidates.
Proteins are the workhorses that keep our cells running, and there are many thousands of types of proteins in our cells, each performing a specialized function. Researchers have long known that the structure of a protein determines what it can do.
