Artificial allosteric protein switches with machine-learning-designed receptors - PubMed
2 hours ago
- #synthetic biology
- #biosensors
- #machine learning
- Machine learning is used to design artificial allosteric protein switches, creating efficient receptors that function without global conformational changes.
- The resulting biosensors detect small molecules, peptides, and proteins, supporting colorimetric, luminescent, and electrochemical outputs, and can form intramolecular YES and AND logic gates.
- Fully synthetic switches combine artificial receptor and reporter domains, with ligand binding reducing conformational entropy to boost catalytic activity, as shown by hydrogen/deuterium exchange mass spectrometry and 19F NMR.
- Practical applications include engineering E. coli for steroid-dependent antibiotic resistance and developing bioelectronic devices for quantifying steroid hormones.
- The research is supported by patents and funding from organizations like the Australian Research Council and the National Science Foundation, with some authors having competing interests in related technologies.