延伸阶段 RNA 聚合酶的精确可解模型

IF 2 4区生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY

Physical biology Pub Date : 2024-11-06 DOI:10.1088/1478-3975/ad899e

Ngo P N Ngoc, Vladimir Belitsky, Gunter M Schütz

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引用次数: 0

摘要

我们对 RNA 聚合酶（RNAP）动力学的马尔可夫模型进行了研究，该模型为{it Escherichia coli} 和酵母 RNAP 的生化实验中观察到的转录延伸过程中的合作推动现象提供了物理解释。为了研究 RNAP 的回溯如何影响合作推动，我们在该模型中加入了 RNAP 的后向（上游）移动。通过对模型进行严格的数学处理，我们推导出了RNAP之间相互静态和动力学相互作用的条件，在这些条件下，反向追踪可以保持合作推动。这是通过精确计算该模型稳态中的几个关键属性实现的，包括两个 RNAP 沿 DNA 模板的前进方向分布以及 RNAP 的平均速度和 ﬂux. .

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An exactly solvable model for RNA polymerase during the elongation stage.

We consider a Markovian model for the kinetics of RNA Polymerase (RNAP) which provides a physical explanation for the phenomenon of cooperative pushing during transcription elongation observed in biochemical experiments onEscherichia coliand yeast RNAP. To study how backtracking of RNAP affects cooperative pushing we incorporate into this model backward (upstream) RNAP moves. With a rigorous mathematical treatment of the model we derive conditions on the mutual static and kinetic interactions between RNAP under which backtracking preserves cooperative pushing. This is achieved by exact computation of several key properties in the steady state of this model, including the distribution of headway between two RNAP along the DNA template and the average RNAP velocity and flux.

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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.