Researchers at Harvard and Northwestern have developed a machine learning method that can design intrinsically disordered proteins with custom properties, addressing nearly 30% of all human proteins ...

The intrinsically disordered proteins (IDPs) do not attain a stable secondary or tertiary structure and rapidly change their conformation, making structure prediction particularly challenging. These ...

The intrinsically disordered proteins (IDPs) do not attain a stable secondary or tertiary structure and rapidly change their conformation, making structure prediction particularly challenging. These ...

Researchers create Disobind, an AI tool predicting protein interactions, advancing disease biology and drug design applications.

Textbooks often depict proteins in one conformation, but real life, as usual, is much messier. While some proteins have stable, unchanging structures, many others have intrinsically disordered regions ...

Deep learning tools for protein design can also be used to create molecules that bind to them. Certain peptides, such as intrinsically disordered proteins (IDPs), are challenging to target due to ...

A milestone in biology has been achieved thanks to artificial intelligence (AI) machine learning and applied physics. A new peer-reviewed study by researchers affiliated with Harvard John A. Paulson ...

A protein engineered by University of Washington scientists wraps around its target. (Institute for Protein Design Image) The wiggly targets known to scientists as “intrinsically disordered proteins” ...

Every function in a cell is associated with a particular protein or group of proteins, typically in a well-defined three-dimensional structure. However, intrinsically disordered regions of proteins ...