基于核酸的分子识别的热力学和动力学定向调节。

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL Small Methods Pub Date : 2024-10-11 DOI:10.1002/smtd.202401102
Yihao Liu, Zihan Zhao, Yuqi Zeng, Minze He, Yifan Lyu, Quan Yuan
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引用次数: 0

摘要

基于核酸的分子识别在生物传感和疾病诊断等多个领域发挥着至关重要的作用。为了达到最佳的检测和分析效果,必须通过调节热力学和动力学特性来调节核酸探针或开关的响应性能,以满足特定的应用要求。然而,热力学和动力学理论对识别性能的影响有时并不明显,相关结论也不直观。为了促进对热力学和动力学理论的深入理解和合理利用,本综述重点介绍了核酸热力学和动力学的标志性成果和最新进展,并总结了基于核酸热力学和动力学的核酸分子识别调控策略。本研究希望这样的综述能为未来核酸探针和开关的开发和优化,以及其他核酸相关领域的进展提供参考和指导。
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Thermodynamics and Kinetics-Directed Regulation of Nucleic Acid-Based Molecular Recognition.

Nucleic acid-based molecular recognition plays crucial roles in various fields like biosensing and disease diagnostics. To achieve optimal detection and analysis, it is essential to regulate the response performance of nucleic acid probes or switches to match specific application requirements by regulating thermodynamics and kinetics properties. However, the impacts of thermodynamics and kinetics theories on recognition performance are sometimes obscure and the relative conclusions are not intuitive. To promote the thorough understanding and rational utilization of thermodynamics and kinetics theories, this review focuses on the landmarks and recent advances of nucleic acid thermodynamics and kinetics and summarizes the nucleic acid thermodynamics and kinetics-based strategies for regulation of nucleic acid-based molecular recognition. This work hopes such a review can provide reference and guidance for the development and optimization of nucleic acid probes and switches in the future, as well as for advancements in other nucleic acid-related fields.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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