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Artificial allosteric protein switches with machine learning-designed receptors

ABSTRACT: Protein allostery underlies most information and energy processing in biology, and the development of artificial allosteric proteins is a key objective of synthetic biology and biotechnology. Our results show that minimalistic ligand-binding domains, engineered by machine learning and lacking ligand-induced global conformational changes, act as efficient synthetic receptors of single-component allosteric protein switches. Such colorimetric, luminescent, and electrochemical biosensors of small molecules, peptides, and proteins can be complied into intramolecular YES and AND logic gates. Furthermore, we report fully synthetic allosteric switches composed of artificial receptor and reporter domains. The results of biophysical experiments including HDX-MS and 19F NMR analysis suggest that ligand-binding reduces conformation entropy of the system increasing catalytic activity of the reporter domain. The practical utility of this approach is demonstrated by engineering E. coli cells with steroid-dependent antibiotic resistance and developing bioelectronic devices capable of quantifying steroid hormones.

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ORGANISM(S): Escherichia Coli

SUBMITTER: Jonathan Phillips

LAB HEAD: Jonathan James Phillips

PROVIDER: PXD073666 | Pride | 2026-04-29

REPOSITORIES: Pride

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			Action	DRS
	20250627_WTB_0ms_CEhigh_01_IA_final_peptide.csv	Csv
	20250627_WTB_0ms_CEvhigh_01_IA_final_peptide.csv	Csv
	20250627_cpBBLA_100000ms_01.raw.zip	Raw
	20250627_cpBBLA_100000ms_02.raw.zip	Raw
	20250627_cpBBLA_100000ms_03.raw.zip	Raw

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