検索対象:     
報告書番号:
※ 半角英数字
 年 ~ 
 年

A New method for evaluating the specificity of indirect readout in protein-DNA recognition

タンパク質-DNA認識における間接認識の特異性を評価する新手法

山崎 智*; 寺田 透*; 河野 秀俊; 清水 謙多郎*; 皿井 明倫*

Yamasaki, Satoshi*; Terada, Toru*; Kono, Hidetoshi; Shimizu, Kentaro*; Sarai, Akinori*

Sequence-specific recognition of DNA by proteins plays a critical role in regulating gene expression. The accurate recognition of target sequences in the genome can be achieved by a combination of two different mechanisms: the direct readout through the direct interactions between protein and DNA bases; and the indirect readout through the sequence-dependent conformation and/or deformability of DNA structure. While the specificity of direct readout has been well characterized, it is rather difficult to assess the contribution of indirect readout to the specificity. In order to quantify the specificity of indirect readout, we have developed a new method. First, we used Bayesian statistics to derive the probability of a particular sequence for a given DNA structure using ensembles obtained by molecular dynamics (MD) simulations of DNAs containing all 136 unique tetramer sequences. Secondly, we used the information entropy to quantify the specificity of indirect readout. We applied this method to protein-DNA complexes of known structures to examine its validity. We could correctly predict those regions where experiments suggested the involvement of indirect readout, and could indicate new regions where the indirect readout mechanism can make major contributions to the recognition. The present probability/entropy-based approach has advantage over the previous energy-based approach in that the trajectories of MD simulation can be directly converted into the probability of sequence and the specificity of indirect readout without any approximation to the distributions in the conformational ensembles of DNA, and would serve as a powerful tool to study the mechanism of protein-DNA recognition.

Access

:

- Accesses

InCites™

:

Altmetrics

:

[CLARIVATE ANALYTICS], [WEB OF SCIENCE], [HIGHLY CITED PAPER & CUP LOGO] and [HOT PAPER & FIRE LOGO] are trademarks of Clarivate Analytics, and/or its affiliated company or companies, and used herein by permission and/or license.