A structural rendering of the ancestral spike protein, the target of the nanobody designs. Unchanged. Image source. Licence.
When a virus changes, a molecule that once fit its surface can lose its grip. In a study published in Nature, researchers gave a team of AI agents a version of that design problem. Could it propose small antibody fragments that would still bind to the spike protein of SARS-CoV-2 as it changed?
The fragments are called nanobodies. The agents assembled a workflow that proposed changes to their protein sequences, predicted the resulting structures and scored the designs. The workflow drew on existing tools including ESM, AlphaFold-Multimer and Rosetta. It produced 92 candidates for the researchers to take into the lab.
A good grip is a result with limits
The paper reports two designs with better binding to the JN.1 or KP.3 variant while preserving strong binding to the ancestral spike protein. Binding is a useful early measurement. It leaves open whether a candidate would prevent infection or work safely as a treatment.
The handoff is the part worth watching. A computational score gave the researchers a way to choose molecules to make. Testing those molecules against physical samples gave them a separate way to see whether the designs deserved more work.