MTA-DE Laboratory of Protein Dynamics, Department of Biochemistry and Molecular Biology, University of Debrecen, Hungary.
MTA-DE Laboratory of Protein Dynamics, Department of Biochemistry and Molecular Biology, University of Debrecen, Hungary; The John Curtin School of Medical Research, The Australian National University, Canberra, ACT, 2601, Australia.
J Mol Biol. 2020 Mar 27;432(7):2289-2303. doi: 10.1016/j.jmb.2020.02.017. Epub 2020 Feb 27.
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.
越来越多的人认识到，紊乱的蛋白质可能是模糊的，因为它们可以表现出各种各样的结合模式。除了众所周知的结合后折叠（无序到有序的转变）过程外，许多相互作用的蛋白质在其结合状态下仍然保持无序的例子也在不断涌现（无序到无序的转变）。此外，无序的蛋白质可能根据其伴侣（上下文相关的结合）在不同程度上占据有序和无序状态。在这里，我们汇集了三个数据集，包括 828 个蛋白质区域的无序到有序、上下文相关和无序到无序的转变，这些区域代表了 2157 个复合物，并阐明了不同相互作用模式的序列决定因素。我们发现，模糊相互作用源于局部序列组成，这些组成促进了广泛的不同结构的采样。基于这一观察结果，我们开发了 FuzPred 方法（http://protdyn-fuzpred.org），该方法可以根据蛋白质的氨基酸序列预测无序蛋白质的结合模式，而无需指定其伴侣。因此，我们展示了蛋白质的氨基酸序列如何在结合时编码广泛的构象变化，包括从无序到有序和从无序到无序状态的转变。
