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基于蛋白质结构静态和动态特征的统计分析重新审视拉马钱德兰图。

Revisiting the Ramachandran plot based on statistical analysis of static and dynamic characteristics of protein structures.

作者信息

Park Soon Woo, Lee Byung Ho, Song Seung Hun, Kim Moon Ki

机构信息

School of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea.

School of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea; SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea.

出版信息

J Struct Biol. 2023 Mar;215(1):107939. doi: 10.1016/j.jsb.2023.107939. Epub 2023 Jan 24.

Abstract

Ramachandran plots, which describe protein structures by plotting the dihedral angle pairs of the backbone on a two-dimensional plane, have played an important role in structural biology over the past few decades. However, despite continued discovery of new protein structures to date, the Ramachandran plot is still constructed by only a small number of data points, and further it cannot reflect the steric information of proteins. Here, we investigated the secondary structure of proteins in terms of static and dynamic characteristics. As for static feature, the Ramachandran plot was revisited for the dataset consisting of 9,148 non-redundant high-resolution protein structures released in the protein data bank until April 1, 2022. By calculating amino acid propensities, it was found that the proportion of secondary structures with respect to residue depth is directly related to their hydrophobicity. As for dynamic feature, normal mode analysis (NMA) based on an elastic network model (ENM) was carried out for the dataset using our KOSMOS web server (http://bioengineering.skku.ac.kr/kosmos/). All ENM-based NMA results were stored in the KOSMOS database, allowing researchers to use them in various ways. In this process, it was commonly found that high B-factors appeared at the edge of the alpha helix region, which was elucidated by introducing residue depth. In addition, by investigating the change in dihedral angle, it was possible to quantitatively survey the contribution of structural change of protein on the Ramachandran plot. In conclusion, our statistical analysis of protein characteristics will provide insight into a range of protein structural studies.

摘要

拉马钱德兰图通过在二维平面上绘制主链的二面角对来描述蛋白质结构,在过去几十年的结构生物学中发挥了重要作用。然而,尽管迄今为止不断有新的蛋白质结构被发现,但拉马钱德兰图仍然仅由少数数据点构建而成,而且它无法反映蛋白质的空间信息。在此,我们从静态和动态特征方面研究了蛋白质的二级结构。关于静态特征,我们重新审视了由蛋白质数据库截至2022年4月1日发布的9148个非冗余高分辨率蛋白质结构组成的数据集的拉马钱德兰图。通过计算氨基酸倾向,发现二级结构相对于残基深度的比例与它们的疏水性直接相关。关于动态特征,我们使用我们的KOSMOS网络服务器(http://bioengineering.skku.ac.kr/kosmos/)对该数据集进行了基于弹性网络模型(ENM)的正常模式分析(NMA)。所有基于ENM的NMA结果都存储在KOSMOS数据库中,使研究人员能够以各种方式使用它们。在此过程中,普遍发现高B因子出现在α螺旋区域的边缘,这通过引入残基深度得到了解释。此外,通过研究二面角的变化,可以定量地考察蛋白质结构变化对拉马钱德兰图的贡献。总之,我们对蛋白质特征的统计分析将为一系列蛋白质结构研究提供见解。

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