BACKGROUND 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. RESULTS 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. CONCLUSION 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.

中文翻译：

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一种基于残差平均距离统计数据构建的平均距离图预测本征杂乱区域的新技术。

背景技术人们长期以来一直认为蛋白质在生理条件下通过其自身的特定3D结构表现出其特定功能。但是，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，即所谓的固有无序蛋白质（IDP）。这项研究基于我们的平均距离图（ADM）技术，提出了一种预测蛋白质内在无序区域的新技术。开发了ADM技术来预测蛋白质中的紧凑区域或结构域。在含有部分无序区域的蛋白质中，一个结构域区域可能是有序的，因此，一个无序区域不太可能成为任何结构域的一部分。因此，预期ADM技术还将预测域之间的无序区域。结果我们的新技术的结果与社区级CASP10实验中表现最好的三种技术相当。我们进一步讨论p53的情况，p53是一种肿瘤抑制蛋白，是细胞周期调控蛋白中最重要的蛋白。当两个p53形成二聚体时，该蛋白质显示出无序的单体特征，但显示出有序特征。结论我们的技术可以预测蛋白质中固有无序区域的位置，其准确性可与目前提出的最佳技术相媲美。此外，它还可以预测通过交互作用（例如二聚化）形成确定的3D结构的IDP核心区域。我们研究中的技术还可以用作预测无序区域的方法，该无序区域在与其他蛋白质结合时会变成有序结构。