A new technique for predicting intrinsically disordered regions based on average distance map constructed with inter-residue average distance statistics

Q3 Biochemistry, Genetics and Molecular Biology BMC Structural Biology Pub Date : 2019-02-06 DOI:10.1186/s12900-019-0101-3
Takumi Shimomura, Kohki Nishijima, Takeshi Kikuchi
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引用次数: 5

Abstract

It had long been thought that a protein exhibits its specific function through its own specific 3D-structure under physiological conditions. However, subsequent research has shown that there are many proteins without specific 3D-structures under physiological conditions, so-called intrinsically disordered proteins (IDPs). This study presents a new technique for predicting intrinsically disordered regions in a protein, based on our average distance map (ADM) technique. The ADM technique was developed to predict compact regions or structural domains in a protein. In a protein containing partially disordered regions, a domain region is likely to be ordered, thus it is unlikely that a disordered region would be part of any domain. Therefore, the ADM technique is expected to also predict a disordered region between domains.

The results of our new technique are comparable to the top three performing techniques in the community-wide CASP10 experiment. We further discuss the case of p53, a tumor-suppressor protein, which is the most significant protein among cell cycle regulatory proteins. This protein exhibits a disordered character as a monomer but an ordered character when two p53s form a dimer.

Our technique can predict the location of an intrinsically disordered region in a protein with an accuracy comparable to the best techniques proposed so far. Furthermore, it can also predict a core region of IDPs forming definite 3D structures through interactions, such as dimerization. The technique in our study may also serve as a means of predicting a disordered region which would become an ordered structure when binding to another protein.

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基于残差平均距离统计构造的平均距离图,提出了一种预测内在无序区域的新方法
长期以来,人们一直认为蛋白质在生理条件下通过其自身特定的3d结构来展示其特定的功能。然而,随后的研究表明,在生理条件下,有许多蛋白质没有特定的3d结构,即所谓的内在无序蛋白质(IDPs)。本研究提出了一种基于平均距离图(ADM)技术预测蛋白质内在无序区域的新技术。ADM技术是用来预测蛋白质中的紧致区域或结构域的。在含有部分无序区域的蛋白质中,结构域区域可能是有序的,因此无序区域不太可能是任何结构域的一部分。因此,预计ADM技术也可以预测域之间的无序区域。我们的新技术的结果与社区范围内CASP10实验中表现最好的三种技术相当。我们进一步讨论了肿瘤抑制蛋白p53的情况,它是细胞周期调节蛋白中最重要的蛋白。当两个p53形成二聚体时,该蛋白表现出无序的特性,而当两个p53形成二聚体时则表现出有序的特性。我们的技术可以预测蛋白质中内在无序区域的位置,其准确性可与目前提出的最佳技术相媲美。此外,它还可以预测IDPs通过相互作用(如二聚化)形成确定的三维结构的核心区域。我们研究中的技术也可以作为一种预测无序区域在与另一种蛋白质结合时将成为有序结构的手段。
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来源期刊
CiteScore
3.60
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: BMC Structural Biology is an open access, peer-reviewed journal that considers articles on investigations into the structure of biological macromolecules, including solving structures, structural and functional analyses, and computational modeling.
期刊最新文献
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