Use of hydrogen deuterium exchange mass spectrometry in tandem with modern structural biology.

IF 4.3 3区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Hunter G Nyvall,Alexandria L Shaw,Emma E Walsh,Hirsh Bhatti,John E Burke
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引用次数: 0

Abstract

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is an established technique that measures the exchange rate of amide hydrogens, with this exchange rate being a surrogate for protein conformational dynamics. Advances in instrumentation, automation, and data analysis have transformed HDX-MS into a high-throughput and highly reproducible method capable of probing complex biological systems and addressing key questions that have been challenging to study by other structural biology approaches. By enabling measurement of amide exchange rates and mapping of differential exchange between distinct conformational states, HDX-MS provides insight into both allosteric transitions and protein interaction interfaces. Recent advances in the capabilities of artificial intelligence (AI) have been rapidly adopted by structural biology, leading to an unprecedented expansion in the quantity and accessibility of structural predictions, underscoring the need for experimental methods to validate these predicted models and provide insight into both epitopes and allosteric conformational changes. This is particularly critical for non-evolutionarily driven interactions such as antibodies, nanobodies, and artificially designed proteins, where AI technologies can yield false positives. This review highlights how HDX-MS can be integrated synergistically into modern structural biology workflows (cryo-EM, X-ray crystallography, and AI-enabled modeling) and how combining these approaches can be powerful to advance our mechanistic understanding of complex biological processes.
使用氢氘交换质谱法串联与现代结构生物学。
氢-氘交换质谱(HDX-MS)是一种测量酰胺氢交换速率的成熟技术,该交换速率是蛋白质构象动力学的替代。仪器、自动化和数据分析的进步已经将HDX-MS转变为一种高通量和高可重复性的方法,能够探测复杂的生物系统,并解决其他结构生物学方法难以研究的关键问题。通过测量酰胺交换率和绘制不同构象状态之间的差异交换,HDX-MS提供了对变构转变和蛋白质相互作用界面的洞察。人工智能(AI)能力的最新进展已被结构生物学迅速采用,导致结构预测的数量和可及性空前扩大,强调需要实验方法来验证这些预测模型,并提供对表位和变构构象变化的见解。这对于非进化驱动的相互作用尤其重要,如抗体、纳米体和人工设计的蛋白质,在这些情况下,人工智能技术可能产生假阳性。这篇综述强调了HDX-MS如何协同集成到现代结构生物学工作流程中(低温电镜、x射线晶体学和人工智能建模),以及如何将这些方法结合起来,有力地推进我们对复杂生物过程的机制理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biochemical Journal
Biochemical Journal 生物-生化与分子生物学
CiteScore
8.00
自引率
0.00%
发文量
255
审稿时长
1 months
期刊介绍: Exploring the molecular mechanisms that underpin key biological processes, the Biochemical Journal is a leading bioscience journal publishing high-impact scientific research papers and reviews on the latest advances and new mechanistic concepts in the fields of biochemistry, cellular biosciences and molecular biology. The Journal and its Editorial Board are committed to publishing work that provides a significant advance to current understanding or mechanistic insights; studies that go beyond observational work using in vitro and/or in vivo approaches are welcomed. Painless publishing: All papers undergo a rigorous peer review process; however, the Editorial Board is committed to ensuring that, if revisions are recommended, extra experiments not necessary to the paper will not be asked for. Areas covered in the journal include: Cell biology Chemical biology Energy processes Gene expression and regulation Mechanisms of disease Metabolism Molecular structure and function Plant biology Signalling
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