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用于研究内在无序蛋白质及其复合物的计算方法。

Computational Methods to Investigate Intrinsically Disordered Proteins and their Complexes.

作者信息

Liu Zi Hao, Tsanai Maria, Zhang Oufan, Forman-Kay Julie, Head-Gordon Teresa

机构信息

Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada.

Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada.

出版信息

ArXiv. 2024 Sep 3:arXiv:2409.02240v1.

Abstract

In 1999 Wright and Dyson highlighted the fact that large sections of the proteome of all organisms are comprised of protein sequences that lack globular folded structures under physiological conditions. Since then the biophysics community has made significant strides in unraveling the intricate structural and dynamic characteristics of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs). Unlike crystallographic beamlines and their role in streamlining acquisition of structures for folded proteins, an integrated experimental and computational approach aimed at IDPs/IDRs has emerged. In this Perspective we aim to provide a robust overview of current computational tools for IDPs and IDRs, and most recently their complexes and phase separated states, including statistical models, physics-based approaches, and machine learning methods that permit structural ensemble generation and validation against many solution experimental data types.

摘要

1999年,赖特(Wright)和戴森(Dyson)强调了这样一个事实:所有生物体蛋白质组的大部分由在生理条件下缺乏球状折叠结构的蛋白质序列组成。从那时起,生物物理学界在揭示内在无序蛋白质(IDP)和内在无序区域(IDR)的复杂结构和动态特征方面取得了重大进展。与晶体学光束线及其在简化折叠蛋白质结构获取中的作用不同,一种针对IDP/IDR的综合实验和计算方法已经出现。在这篇观点文章中,我们旨在全面概述当前用于IDP和IDR的计算工具,以及最近针对它们的复合物和相分离状态的计算工具,包括统计模型、基于物理的方法和机器学习方法,这些方法允许生成结构集合并针对多种溶液实验数据类型进行验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f7e/11398552/fa3ae2555473/nihpp-2409.02240v1-f0001.jpg

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