Department of Biochemistry and Molecular Biology, Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, TX 77555, USA.
Department of Chemistry, Department of Chemical and Biomolecular Engineering, Department of Physics and Astronomy and Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA.
Biophys Chem. 2021 Feb;269:106521. doi: 10.1016/j.bpc.2020.106521. Epub 2020 Dec 10.
To perform their functions, transcription factors and DNA-repair/modifying enzymes randomly search DNA in order to locate their specific targets on DNA. Discrete-state stochastic kinetic models have been developed to explain how the efficiency of the search process is influenced by the molecular properties of proteins and DNA as well as by other factors such as molecular crowding. These theoretical models not only offer explanations on the relation of microscopic processes to macroscopic behavior of proteins, but also facilitate the analysis and interpretation of experimental data. In this review article, we provide an overview on discrete-state stochastic kinetic models and explain how these models can be applied to experimental investigations using stopped-flow, single-molecule, nuclear magnetic resonance (NMR), and other biophysical and biochemical methods.
为了发挥其功能,转录因子和 DNA 修复/修饰酶随机搜索 DNA,以便在 DNA 上定位其特定的靶标。离散状态随机动力学模型已经被开发出来,以解释搜索过程的效率如何受到蛋白质和 DNA 的分子特性以及分子拥挤等其他因素的影响。这些理论模型不仅提供了关于微观过程与蛋白质宏观行为之间关系的解释,而且还便于分析和解释实验数据。在这篇综述文章中,我们提供了离散状态随机动力学模型的概述,并解释了如何将这些模型应用于使用停流、单分子、核磁共振(NMR)和其他生物物理和生物化学方法进行的实验研究。