由LacI拓扑结构引导的工程变构转录因子。

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Ashley N Hersey, Valerie E Kay, Sumin Lee, Matthew J Realff, Corey J Wilson
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引用次数: 1

摘要

变构转录因子(aTFs)在整个生物学和生物技术的无数过程中使用。atf已成为合成生物学、基础研究和蛋白质制造领域发展的主力。最常用的tf之一是乳糖抑制因子(LacI)。除了作为基因调控的特殊工具外,LacI还作为理解变构通讯的杰出模型系统。从这个角度来看,我们将使用LacI TF作为与变构相关的工程替代功能的主要范例。交替的蛋白质DNA相互作用,交替的蛋白质配体相互作用,以及交替的表型机制。此外,我们将总结每个设计目标的设计规则和启发式方法,并演示如何将结果设计规则和启发式方法外推到具有类似拓扑的其他atf中。来自更广泛的LacI/GalR TFs家族。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Engineering allosteric transcription factors guided by the LacI topology.

Engineering allosteric transcription factors guided by the LacI topology.

Allosteric transcription factors (aTFs) are used in a myriad of processes throughout biology and biotechnology. aTFs have served as the workhorses for developments in synthetic biology, fundamental research, and protein manufacturing. One of the most utilized TFs is the lactose repressor (LacI). In addition to being an exceptional tool for gene regulation, LacI has also served as an outstanding model system for understanding allosteric communication. In this perspective, we will use the LacI TF as the principal exemplar for engineering alternate functions related to allostery-i.e., alternate protein DNA interactions, alternate protein-ligand interactions, and alternate phenotypic mechanisms. In addition, we will summarize the design rules and heuristics for each design goal and demonstrate how the resulting design rules and heuristics can be extrapolated to engineer other aTFs with a similar topology-i.e., from the broader LacI/GalR family of TFs.

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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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