Tradeoffs in the design of RNA thermometers.

IF 2 4区生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY

Physical biology Pub Date : 2024-07-10 DOI:10.1088/1478-3975/ad5d6b

Krishan Kumar Gola, Abhilash Patel, Shaunak Sen

引用次数: 0

Abstract

The synthesis of RNA thermometers is aimed at achieving temperature responses with desired thresholds and sensitivities. Although previous works have generated thermometers with a variety of thresholds and sensitivities as well as guidelines for design, possible constraints in the achievable thresholds and sensitivities remain unclear. We addressed this issue using a two-state model and its variants, as well as melt profiles generated from thermodynamic computations. In the two-state model, we found that the threshold was inversely proportional to the sensitivity, in the case of a fixed energy difference between the two states. Notably, this constraint could persist in variations of the two-state model with sequentially unfolding states and branched parallel pathways. Furthermore, the melt profiles generated from a library of thermometers exhibited a similar constraint. These results should inform the design of RNA thermometers as well as other responses that are mediated in a similar fashion.

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RNA 温度计设计中的取舍。

合成 RNA 温度计的目的是获得具有所需阈值和灵敏度的温度响应。虽然以前的工作已经生成了具有各种阈值和灵敏度的温度计以及设计指南，但在可实现的阈值和灵敏度方面可能存在的限制仍不清楚。我们利用双态模型及其变体，以及热力学计算生成的熔融曲线来解决这一问题。在双态模型中，我们发现在两种状态之间能量差固定的情况下，阈值与灵敏度成反比。值得注意的是，在双态模型的变体中，如果存在顺序展开的状态和分支并行途径，这种约束条件就会持续存在。此外，从温度计库中生成的熔融曲线也表现出类似的约束。这些结果将有助于设计 RNA 温度计以及以类似方式介导的其他反应。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Physical biology 生物-生物物理

CiteScore

4.20

自引率

0.00%

发文量

审稿时长

3 months

期刊介绍： Physical Biology publishes articles in the broad interdisciplinary field bridging biology with the physical sciences and engineering. This journal focuses on research in which quantitative approaches – experimental, theoretical and modeling – lead to new insights into biological systems at all scales of space and time, and all levels of organizational complexity. Physical Biology accepts contributions from a wide range of biological sub-fields, including topics such as: molecular biophysics, including single molecule studies, protein-protein and protein-DNA interactions subcellular structures, organelle dynamics, membranes, protein assemblies, chromosome structure intracellular processes, e.g. cytoskeleton dynamics, cellular transport, cell division systems biology, e.g. signaling, gene regulation and metabolic networks cells and their microenvironment, e.g. cell mechanics and motility, chemotaxis, extracellular matrix, biofilms cell-material interactions, e.g. biointerfaces, electrical stimulation and sensing, endocytosis cell-cell interactions, cell aggregates, organoids, tissues and organs developmental dynamics, including pattern formation and morphogenesis physical and evolutionary aspects of disease, e.g. cancer progression, amyloid formation neuronal systems, including information processing by networks, memory and learning population dynamics, ecology, and evolution collective action and emergence of collective phenomena.