Creation and discovery of ligand–receptor pairs for transcriptional control with small molecules
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Schwimmer, Lauren J., Priyanka Rohatgi, Bahareh Azizi, Katherine L. Seley, and Donald F. Doyle. “Creation and Discovery of Ligand–Receptor Pairs for Transcriptional Control with Small Molecules.” Proceedings of the National Academy of Sciences 101, no. 41 (October 12, 2004): 14707–12. https://doi.org/10.1073/pnas.0400884101.
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Abstract
The nuclear receptor retinoid X receptor (RXR) is a ligand-activated transcription factor. To create receptors for a new ligand, a structure-based approach was used to generate a library of ≈380,000 mutant RXR genes. To discover functional variants within the library, we used chemical complementation, a method of protein engineering that uses the power of genetic selection. Wild-type RXR has an EC₅₀ of 500 nM for 9-cis retinoic acid (9cRA) and an EC₅₀ of >10 μM for the synthetic retinoid-like compound LG335 in yeast. The library produced ligand–receptor pairs with LG335 that have a variety of EC₅₀ values (40 nM to >2 μM) and activation levels (10–80% of wild-type RXR with 9cRA) in yeast. The variant I268V;A272V;I310L;F313M has an EC₅₀ for LG335 of 40 nM and an EC₅₀ for 9cRA of >10 μM in yeast. This variant has essentially the reverse ligand specificity of wild-type RXR and is transcriptionally active at a 10-fold-lower ligand concentration in yeast. This EC₅₀ is 25-fold lower than the best receptor we have engineered through site-directed mutagenesis, Q275C;I310M;F313I. Furthermore, the variants' EC₅₀ values and activation levels in yeast and mammalian cells correlate. This protein engineering method should be extendable to produce other functional ligand–receptor pairs, which can be selected and characterized from libraries within weeks. Coupling large library construction with chemical complementation could be used to engineer proteins that bind virtually any small molecule for conditional gene expression, applications in metabolic engineering, and biosensors and to engineer enzymes through genetic selection.