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髓鞘主要致密线的内在无序蛋白胶:将AlphaFold2预测与实验数据联系起来。

The intrinsically disordered protein glue of the myelin major dense line: Linking AlphaFold2 predictions to experimental data.

作者信息

Krokengen Oda C, Raasakka Arne, Kursula Petri

机构信息

Department of Biomedicine, University of Bergen, Norway.

Faculty of Biochemistry and Molecular Medicine & Biocenter Oulu, Oulu, Finland.

出版信息

Biochem Biophys Rep. 2023 Apr 26;34:101474. doi: 10.1016/j.bbrep.2023.101474. eCollection 2023 Jul.

Abstract

Numerous human proteins are classified as intrinsically disordered proteins (IDPs). Due to their physicochemical properties, high-resolution structural information about IDPs is generally lacking. On the other hand, IDPs are known to adopt local ordered structures upon interactions with other proteins or lipid membrane surfaces. While recent developments in protein structure prediction have been revolutionary, their impact on IDP research at high resolution remains limited. We took a specific example of two myelin-specific IDPs, the myelin basic protein (MBP) and the cytoplasmic domain of myelin protein zero (P0ct). Both of these IDPs are crucial for normal nervous system development and function, and while they are disordered in solution, upon membrane binding, they partially fold into helices, being embedded into the lipid membrane. We carried out AlphaFold2 predictions of both proteins and analysed the models in light of experimental data related to protein structure and molecular interactions. We observe that the predicted models have helical segments that closely correspond to the membrane-binding sites on both proteins. We furthermore analyse the fits of the models to synchrotron-based X-ray scattering and circular dichroism data from the same IDPs. The models are likely to represent the membrane-bound state of both MBP and P0ct, rather than the conformation in solution. Artificial intelligence-based models of IDPs appear to provide information on the ligand-bound state of these proteins, instead of the conformers dominating free in solution. We further discuss the implications of the predictions for mammalian nervous system myelination and their relevance to understanding disease aspects of these IDPs.

摘要

许多人类蛋白质被归类为内在无序蛋白质(IDP)。由于其物理化学性质,通常缺乏关于IDP的高分辨率结构信息。另一方面,已知IDP在与其他蛋白质或脂质膜表面相互作用时会形成局部有序结构。虽然蛋白质结构预测的最新进展具有革命性,但它们在高分辨率IDP研究中的影响仍然有限。我们以两种髓鞘特异性IDP为例,即髓鞘碱性蛋白(MBP)和髓鞘蛋白零的细胞质结构域(P0ct)。这两种IDP对正常神经系统发育和功能都至关重要,虽然它们在溶液中是无序的,但在膜结合时,它们会部分折叠成螺旋结构,嵌入脂质膜中。我们对这两种蛋白质进行了AlphaFold2预测,并根据与蛋白质结构和分子相互作用相关的实验数据对模型进行了分析。我们观察到,预测模型中的螺旋片段与这两种蛋白质上的膜结合位点密切对应。我们还进一步分析了模型与来自相同IDP的基于同步加速器的X射线散射和圆二色性数据的拟合情况。这些模型可能代表了MBP和P0ct的膜结合状态,而不是溶液中的构象。基于人工智能的IDP模型似乎提供了这些蛋白质配体结合状态的信息,而不是溶液中占主导地位的自由构象。我们进一步讨论了这些预测对哺乳动物神经系统髓鞘形成的影响及其与理解这些IDP疾病方面的相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32e4/10160357/8e0a11649f28/gr1.jpg

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