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利用序列的固有无序区域预测蛋白质-蛋白质相互作用。

Prediction of protein-protein interactions using sequences of intrinsically disordered regions.

机构信息

Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195, Berlin, Germany.

出版信息

Proteins. 2023 Jul;91(7):980-990. doi: 10.1002/prot.26486. Epub 2023 Mar 20.

Abstract

Protein-protein interactions (PPIs) play a crucial role in numerous molecular processes. Despite many efforts, mechanisms governing molecular recognition between interacting proteins remain poorly understood and it is particularly challenging to predict from sequence whether two proteins can interact. Here we present a new method to tackle this challenge using intrinsically disordered regions (IDRs). IDRs are protein segments that are functional despite lacking a single invariant three-dimensional structure. The prevalence of IDRs in eukaryotic proteins suggests that IDRs are critical for interactions. To test this hypothesis, we predicted PPIs using IDR sequences in candidate proteins in humans. Moreover, we divide the PPI prediction problem into two specific subproblems and adapt appropriate training and test strategies based on problem type. Our findings underline the importance of defining clearly the problem type and show that sequences encoding IDRs can aid in predicting specific features of the protein interaction network of intrinsically disordered proteins. Our findings further suggest that accounting for IDRs in future analyses should accelerate efforts to elucidate the eukaryotic PPI network.

摘要

蛋白质-蛋白质相互作用(PPIs)在许多分子过程中起着至关重要的作用。尽管已经做了很多努力,但对于控制相互作用蛋白质之间分子识别的机制仍了解甚少,并且很难仅从序列预测两个蛋白质是否可以相互作用。在这里,我们提出了一种使用无规卷曲区域(IDRs)来解决此挑战的新方法。IDR 是尽管缺乏单一不变的三维结构但仍具有功能的蛋白质片段。真核蛋白质中 IDR 的普遍性表明 IDR 对于相互作用至关重要。为了验证这一假设,我们使用人类候选蛋白质中的 IDR 序列预测了蛋白质-蛋白质相互作用。此外,我们将 PPI 预测问题分为两个特定的子问题,并根据问题类型采用适当的训练和测试策略。我们的研究结果强调了明确定义问题类型的重要性,并表明编码 IDR 的序列可以帮助预测无规卷曲蛋白质的蛋白质相互作用网络的特定特征。我们的研究结果进一步表明,在未来的分析中考虑 IDR 应该加速阐明真核 PPI 网络的努力。

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