Cagla Ergun Ayva
Exploring performance parameters of artificial allosteric protein switches
Journal title : Journal of Molecular Biology
Publisher : Elsevier BV
Print ISSN : 0022-2836
Page Number : 167678
Journal volume : 434
Journal issue : 17
431 Views Research reports
Biological information processing networks rely on allosteric protein switches that dynamically interconvert biological signals. Construction of their artificial analogues is a central goal of synthetic biology and bioengineering. Receptor domain insertion is one of the leading methods for constructing chimeric protein switches. Here we present an in vitro expression-based platform for the analysis of chimeric protein libraries for which traditional cell survival or cytometric high throughput assays are not applicable. We utilise this platform to screen a focused library of chimeras between PQQ-glucose dehydrogenase and calmodulin. Using this approach, we identified 50 chimeras (approximately 23% of the library) that were activated by calmodulin-binding peptides. We analysed performance parameters of the active chimeras and demonstrated that their dynamic range and response times are anticorrelated, pointing to the existence of an inherent thermodynamic trade-off. We show that the structure of the ligand peptide affects both the response and activation kinetics of the biosensors suggesting that the structure of a ligand:receptor complex can influence the chimera's activation pathway. In order to understand the extent of structural changes in the reporter protein induced by the receptor domains, we have analysed one of the chimeric molecules by CD spectroscopy and hydrogen-deuterium exchange mass spectrometry. We concluded that subtle ligand-induced changes in the receptor domain propagated into the GDH domain and affected residues important for substrate and cofactor binding. Finally, we used one of the identified chimeras to construct a two-component rapamycin biosensor and demonstrated that core switch optimisation translated into improved biosensor performance.
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DOI : https://doi.org/10.1016/j.jmb.2022.167678
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