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AlphaFold 和淀粉样蛋白景观。

AlphaFold and the amyloid landscape.

机构信息

Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain; Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.

Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain; Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.

出版信息

J Mol Biol. 2021 Oct 1;433(20):167059. doi: 10.1016/j.jmb.2021.167059. Epub 2021 May 21.

Abstract

Protein aggregation is a widespread phenomenon with important implications in many scientific areas. Although amyloid formation is typically considered as detrimental, functional amyloids that perform physiological roles have been identified in all kingdoms of life. Despite their functional and pathological relevance, the structural details of the majority of molecular species involved in the amyloidogenic process remains elusive. Here, we explore the application of AlphaFold, a highly accurate protein structure predictor, in the field of protein aggregation. While we envision a straightforward application of AlphaFold in assisting the design of globular proteins with improved solubility for biomedical and industrial purposes, the use of this algorithm for predicting the structure of aggregated species seems far from trivial. First, in amyloid diseases, the presence of multiple amyloid polymorphs and the heterogeneity of aggregation intermediates challenges the "one sequence, one structure" paradigm, inherent to sequence-based predictions. Second, aberrant aggregation is not the subject of positive selective pressure, precluding the use of evolutionary-based approaches, which are the core of the AlphaFold pipeline. Instead, amyloid polymorphism seems to be constrained by the need for a defined structure-activity relationship in functional amyloids. They may thus provide a starting point for the application of AlphaFold in the amyloid landscape.

摘要

蛋白质聚集是一种广泛存在的现象,在许多科学领域都具有重要意义。尽管淀粉样蛋白的形成通常被认为是有害的,但在所有生命领域都已经发现了具有生理功能的功能性淀粉样蛋白。尽管它们具有功能和病理相关性,但涉及淀粉样蛋白形成过程的大多数分子物种的结构细节仍然难以捉摸。在这里,我们探讨了 AlphaFold 这一高度精确的蛋白质结构预测器在蛋白质聚集领域的应用。虽然我们设想将 AlphaFold 直接应用于辅助设计具有改善的生物医学和工业用途的可溶性的球状蛋白质,但该算法在预测聚集态物种的结构方面的应用似乎远非微不足道。首先,在淀粉样蛋白疾病中,多种淀粉样蛋白多态性的存在和聚集中间体的异质性挑战了基于序列预测的“一个序列,一个结构”的范例。其次,异常聚集不是正选择压力的主题,排除了基于进化的方法的应用,而进化方法是 AlphaFold 管道的核心。相反,淀粉样蛋白多态性似乎受到功能性淀粉样蛋白中定义的结构-活性关系的需要的限制。因此,它们可能为在淀粉样蛋白领域应用 AlphaFold 提供了一个起点。

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