How to measure the probability of uracil chain tautomers as nucleotide bases in RNA?

IF 2.7 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Biomolecular Structure & Dynamics Pub Date : 2024-11-19 DOI:10.1080/07391102.2024.2428827
Parisa Fereidounpour, Shapour Ramazani
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Abstract

The current research focuses on exploring tautomerism in uracil. 47 tautomers were found that varied in significance in RNA and stability. To discover these molecules, diverse potential energy levels were explored, and corresponding transition states were found in these pathways. But the imperative thing that was taken note in this investigation is that for the first time, a method was detailed for the probability of forming distinctive molecules relative to each other. In this method, the conversion of uracil and its tautomers, which together turn into 47 molecules, was composed as a Markov chain. Then, the transition matrix was explained using its support, whose components are the probability of creating molecules from each step. At last, by multiplying this matrix by n times, the probability of forming different molecules was obtained. Moreover, by solving this matrix at different times, it is conceivable to appear which molecules can be converted to uracil sooner. It was appeared that a few tautomers act as transitory absorption point or temporary terminal states and other molecules, to begin with convert to these molecules before turning into uracil.

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如何测量 RNA 中作为核苷酸碱基的尿嘧啶链同系物的概率?
目前的研究重点是探索尿嘧啶的同分异构体。研究发现了 47 种在 RNA 和稳定性方面意义不同的同分异构体。为了发现这些分子,研究人员探索了不同的潜在能级,并在这些途径中发现了相应的过渡态。但在这项研究中必须注意的是,首次详细说明了形成彼此不同分子的概率的方法。在这种方法中,尿嘧啶及其同素异形体的转化(它们一起转化成 47 个分子)组成了一个马尔科夫链。然后,利用转换矩阵的支持来解释转换矩阵,其组成部分是每一步产生分子的概率。最后,将该矩阵乘以 n 次,就得到了形成不同分子的概率。此外,通过在不同时间求解该矩阵,可以想象出哪些分子可以更快地转化为尿嘧啶。结果表明,有几种同系物充当过渡吸收点或暂时末端状态,其他分子在转化为尿嘧啶之前,首先会转化为这些分子。
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来源期刊
Journal of Biomolecular Structure & Dynamics
Journal of Biomolecular Structure & Dynamics 生物-生化与分子生物学
CiteScore
8.90
自引率
9.10%
发文量
597
审稿时长
2 months
期刊介绍: The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.
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