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探索蛋白激酶的构象景观。

Exploring the conformational landscape of protein kinases.

机构信息

Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA. Electronic address: https://twitter.com/NancyRGough.

Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.

出版信息

Curr Opin Struct Biol. 2024 Oct;88:102890. doi: 10.1016/j.sbi.2024.102890. Epub 2024 Jul 22.

DOI:10.1016/j.sbi.2024.102890
PMID:39043011
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11694674/
Abstract

Protein kinases are dynamic enzymes that display complex regulatory mechanisms. Although they possess a structurally conserved catalytic domain, significant conformational dynamics are evident both within a single kinase and across different kinases in the kinome. Here, we highlight methods for exploring this conformational space and its dynamics using kinase domains from ABL1 (Abelson kinase), PKA (protein kinase A), AurA (Aurora A), and PYK2 (proline-rich tyrosine kinase 2) as examples. Such experimental approaches combined with AI-driven methods, such as AlphaFold, will yield discoveries about kinase regulation, the catalytic process, substrate specificity, the effect of disease-associated mutations, as well as new opportunities for structure-based drug design.

摘要

蛋白激酶是具有复杂调节机制的动态酶。尽管它们具有结构上保守的催化结构域，但在单个激酶和激酶组中的不同激酶中，都存在明显的构象动力学。在这里，我们以 ABL1（Abelson 激酶）、PKA（蛋白激酶 A）、AurA（Aurora A）和 PYK2（富含脯氨酸的酪氨酸激酶 2）的激酶结构域为例，强调了探索这种构象空间及其动力学的方法。此类实验方法与 AI 驱动的方法（如 AlphaFold）相结合，将产生关于激酶调节、催化过程、底物特异性、与疾病相关突变的影响以及基于结构的药物设计的新机会的发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/391f/11694674/15c0d45850f1/nihms-2042749-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/391f/11694674/05910b1c6c17/nihms-2042749-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/391f/11694674/0e7852b32828/nihms-2042749-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/391f/11694674/15c0d45850f1/nihms-2042749-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/391f/11694674/05910b1c6c17/nihms-2042749-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/391f/11694674/0e7852b32828/nihms-2042749-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/391f/11694674/15c0d45850f1/nihms-2042749-f0004.jpg

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2
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Bioinform Adv. 2023 Sep 15;3(1):vbad129. doi: 10.1093/bioadv/vbad129. eCollection 2023.
3
De novo design of protein structure and function with RFdiffusion.利用 RFdiffusion 从头设计蛋白质结构和功能。
Nature. 2023 Aug;620(7976):1089-1100. doi: 10.1038/s41586-023-06415-8. Epub 2023 Jul 11.
4
Evolutionary-scale prediction of atomic-level protein structure with a language model.用语言模型进行原子级蛋白质结构的进化尺度预测。
Science. 2023 Mar 17;379(6637):1123-1130. doi: 10.1126/science.ade2574. Epub 2023 Mar 16.
5
An NMR portrait of functional and dysfunctional allosteric cooperativity in cAMP-dependent protein kinase A.NMR 描绘 cAMP 依赖性蛋白激酶 A 的功能和非功能变构协同性。
FEBS Lett. 2023 Apr;597(8):1055-1072. doi: 10.1002/1873-3468.14610. Epub 2023 Mar 26.
6
Activation loop phosphorylation tunes conformational dynamics underlying Pyk2 tyrosine kinase activation.激活环磷酸化调节Pyk2酪氨酸激酶激活背后的构象动力学。
Structure. 2023 Apr 6;31(4):447-454.e5. doi: 10.1016/j.str.2023.02.003. Epub 2023 Mar 3.
7
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