Protein design aims to create customized antibodies for therapies, biosensors for diagnostics, or enzymes for chemical reactions. An international research team has now developed a method for designing large new proteins better than before and producing them with the desired properties in the laboratory.
Their approach involves a new way of using the capabilities of the AI-based software Alphafold2, for which the Nobel Prize in Chemistry was awarded in 2024.
Whether as building blocks, transport systems, enzymes, or antibodies, proteins play a vital role in our bodies. Researchers are, therefore, trying to recreate them or to design so-called de novo proteins that do not occur in nature. Such artificial proteins are designed to bind to certain viruses or transport drugs, for example. Scientists are increasingly using machine learning to design them.
"We have designed the process for new proteins so that we initially ignore the limits of what is physically possible. Usually, only one of the 20 possible building blocks is assumed at each point of the amino acid chain. Instead, we use a variant in which all possibilities are virtually superimposed," says Christopher Frank, doctoral candidate at the Chair of Biomolecular Nanotechnology and first author of the study.
Using their new method, they were able to produce proteins consisting of up to 1000 amino acids."This brings us closer to the size of antibodies, and - just as with antibodies - we can then integrate several desired functions into such a protein," explains Hendrik Dietz."These could, for example, be motifs for recognizing and suppressing pathogens.
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