Published in the journal Angewandte Chemie, the AF-CBA system provides unprecedented speed and sensitivity in identifying the strongest molecules (peptides) that bind to a given protein. This is very important because protein interactions play a key role in the development of various diseases.
The conveyor operates like a “busy grocery store.” Imagine comparing each fruit to find the ripest one. Traditional methods are similar to testing multiple options manually. However, AF-CBA uses artificial intelligence to model the interaction between thousands of potential molecules and the target protein, identifying the best option in a very short time.
The beauty of AF-CBA is that it is accessible. It relies on AlphaFold, a well-established program from Google DeepMind that uses deep learning to predict the structure of proteins. This familiarity with existing technology paves the way for its wider use by researchers.
The team won’t stop there. They plan to use AF-CBA to further study diseases and suppress harmful agents. Currently, their targets are two viruses: murine leukemia virus and Kaposi’s sarcoma virus. Both interact with unknown proteins and can lead to serious health problems, including tumors.
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Source: Ferra
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