Suppr超能文献

配体特异性生物传感技术在结构相似分子分析中的进展。

Advances in ligand-specific biosensing for structurally similar molecules.

机构信息

Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA.

Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA; Division of Biology and Biomedical Sciences, Washington University in St. Louis, St. Louis, MO, USA.

出版信息

Cell Syst. 2023 Dec 20;14(12):1024-1043. doi: 10.1016/j.cels.2023.10.009.

Abstract

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

摘要

生物系统的特异性使得有可能开发针对复杂医学或环境样品中特定代谢物、毒素和污染物的生物传感器,而不会受到结构相似化合物的干扰。在过去的二十年中,人们通过合成生物学策略致力于创造具有新颖特性的蛋白质或核酸。除了增强生物催化活性、扩大目标底物范围、提高酶的对映选择性和稳定性之外,越来越多的研究领域是增强遗传编码生物传感器的分子特异性。在这里,我们总结了开发高特异性生物传感器系统及其重要应用的最新进展。首先,我们描述了创建包含低混杂性或更好特异性的潜在突变体文库所需的合理设计原则。接下来,我们回顾了新兴的高通量筛选技术,以针对所需的目标工程生物传感特异性。最后,我们研究了计算机辅助评估和预测方法,以促进配体特异性生物传感器的构建。

相似文献

2
Genetically Encoded Biosensor Engineering for Application in Directed Evolution.基因编码生物传感器工程在定向进化中的应用。
J Microbiol Biotechnol. 2023 Oct 28;33(10):1257-1267. doi: 10.4014/jmb.2304.04031. Epub 2023 Jul 14.
3
Biosensor-guided discovery and engineering of metabolic enzymes.生物传感器引导的代谢酶的发现和工程改造。
Biotechnol Adv. 2023 Dec;69:108251. doi: 10.1016/j.biotechadv.2023.108251. Epub 2023 Sep 9.
5
Mining and design of biosensors for engineering microbial cell factory.生物传感器的挖掘和设计用于工程微生物细胞工厂。
Curr Opin Biotechnol. 2022 Jun;75:102694. doi: 10.1016/j.copbio.2022.102694. Epub 2022 Feb 11.

本文引用的文献

2
Luciferase-Based Biosensors in the Era of the COVID-19 Pandemic.新冠疫情时代基于荧光素酶的生物传感器
ACS Nanosci Au. 2021 Aug 9;1(1):15-37. doi: 10.1021/acsnanoscienceau.1c00009. eCollection 2021 Dec 15.
6
The Impact of Supervised Learning Methods in Ultralarge High-Throughput Docking.监督学习方法在超高通量对接中的影响。
J Chem Inf Model. 2023 Apr 24;63(8):2267-2280. doi: 10.1021/acs.jcim.2c01471. Epub 2023 Apr 10.
9
De novo design of luciferases using deep learning.利用深度学习进行荧光素酶的从头设计。
Nature. 2023 Feb;614(7949):774-780. doi: 10.1038/s41586-023-05696-3. Epub 2023 Feb 22.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验