It is becoming increasingly recognised that disordered proteins may be fuzzy, in that they can exhibit a wide variety of binding modes. In addition to the well-known process of folding upon binding (disorder-to-order transition), many examples are emerging of interacting proteins that remain disordered in their bound states (disorder-to-disorder transitions). Furthermore, disordered proteins may populate ordered and disordered states to different extents depending on their partners (context-dependent binding). Here we assemble three datasets comprising disorder-to-order, context-dependent, and disorder-to-disorder transitions of 828 protein regions represented in 2157 complexes and elucidate the sequence-determinants of the different interaction modes. We found that fuzzy interactions originate from local sequence compositions that promote the sampling of a wide range of different structures. Based on this observation, we developed the FuzPred method (http://protdyn-fuzpred.org) of predicting the binding modes of disordered proteins based on their amino acid sequences, without specifying their partners. We thus illustrate how the amino acid sequences of proteins can encode a wide range of conformational changes upon binding, including transitions from disordered to ordered and from disordered to disordered states.

中文翻译：

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模糊蛋白质相互作用的基于序列的预测。

越来越多地认识到无序蛋白可能是模糊的，因为它们可以表现出多种结合模式。除了众所周知的结合时折叠的过程（无序过渡），许多相互作用蛋白的例子也不断出现，这些蛋白在其结合状态（无序过渡）保持无序。此外，无序蛋白可能会根据其配偶体（上下文依赖性结合）而在不同程度上填充有序状态和无序状态。在这里，我们组装了三个数据集，包括2157个复合体中表示的828个蛋白区域的无序排列，上下文相关和无序过渡，并阐明了不同相互作用模式的序列决定因素。我们发现模糊的相互作用源于局部序列组成，其促进了各种不同结构的采样。基于此观察，我们开发了FuzPred方法（http://protdyn-fuzpred.org），该方法可根据无序蛋白的氨基酸序列预测无序蛋白的结合模式，而无需指定其伴侣。因此，我们说明了蛋白质的氨基酸序列如何在结合后编码广泛的构象变化，包括从无序到有序以及从无序到无序状态的转变。