Engineering Allostery

Overview

Journal Trends Genet

Specialty Genetics

Date 2014 Oct 13

PMID 25306102

Citations 32

Authors

Srivatsan Raman

Noah Taylor

Naomi Genuth

Stanley Fields

George M Church

Affiliations

Soon will be listed here.

Abstract

Allosteric proteins have great potential in synthetic biology, but our limited understanding of the molecular underpinnings of allostery has hindered the development of designer molecules, including transcription factors with new DNA-binding or ligand-binding specificities that respond appropriately to inducers. Such allosteric proteins could function as novel switches in complex circuits, metabolite sensors, or as orthogonal regulators for independent, inducible control of multiple genes. Advances in DNA synthesis and next-generation sequencing technologies have enabled the assessment of millions of mutants in a single experiment, providing new opportunities to study allostery. Using the classic LacI protein as an example, we describe a genetic selection system using a bidirectional reporter to capture mutants in both allosteric states, allowing the positions most crucial for allostery to be identified. This approach is not limited to bacterial transcription factors, and could reveal new mechanistic insights and facilitate engineering of other major classes of allosteric proteins such as nuclear receptors, two-component systems, G protein-coupled receptors, and protein kinases.

Citing Articles

Engineering and application of LacI mutants with stringent expressions.

Wu J, Liang C, Li Y, Zeng Y, Sun X, Jiang P Microb Biotechnol. 2024; 17(3):e14427.

PMID: 38465475 PMC: 10926051. DOI: 10.1111/1751-7915.14427.

Creation of a point-of-care therapeutics sensor using protein engineering, electrochemical sensing and electronic integration.

Cai R, Ngwadom C, Saxena R, Soman J, Bruggeman C, Hickey D Nat Commun. 2024; 15(1):1689.

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Target-dependent RNA polymerase as universal platform for gene expression control in response to intracellular molecules.

Komatsu S, Ohno H, Saito H Nat Commun. 2023; 14(1):7256.

PMID: 37978180 PMC: 10656481. DOI: 10.1038/s41467-023-42802-5.

Analysis of the Association of Two SNPs in the Promoter Regions of the and Genes with Litter Size in Yunshang Black Goats.

Wang P, Li W, Liu Z, He X, Lan R, Liu Y Animals (Basel). 2022; 12(20).

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Directed Evolution of Transcription Factor-Based Biosensors for Altered Effector Specificity.

Machado L, Dixon N Methods Mol Biol. 2022; 2461:175-193.

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