配体扩散结合到蛋白质靶点,作为蛋白质相互作用的抑制剂。

IF 3.6 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
PLoS Computational Biology Pub Date : 2025-09-17 eCollection Date: 2025-09-01 DOI:10.1371/journal.pcbi.1013495
William Jeffries, Bryan M Delfing, Xavier E Laracuente, Xingyu Luo, Audrey Olson, Kenneth W Foreman, Kyung Hyeon Lee, Greg Petruncio, Vito De Benedictis, Mikell Paige, Kylene Kehn-Hall, Christopher Lockhart, Dmitri K Klimov
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引用次数: 0

摘要

委内瑞拉马脑炎病毒(VEEV)衣壳蛋白核定位信号(NLS)序列与输入蛋白α转运蛋白结合,阻断核输入。预防NLS病毒与输入蛋白α结合可能是一种可行的治疗途径。在这里,我们研究了两种扩散结合抑制剂DP9和dp90干扰VEEV的NLS肽与输入蛋白α结合的分子机制。本研究采用全原子复制交换分子动力学模拟,探讨了VEEV NLS片段、coreNLS肽和进口蛋白-α抑制剂之间的竞争结合。我们之前对coreNLS的非竞争性结合的模拟作为参考,其中coreNLS与进口α天然结合。这两种抑制剂都能消除天然肽结合并减少其天然相互作用的比例,但它们不能阻止其与输入蛋白α的非天然结合。因此,这些抑制剂将coreNLS转变为弥漫性结合剂,其采用多种非天然结合姿势。来自抑制剂的竞争降低了coreNLS与进口蛋白α结合的自由能,表明它们降低了其结合亲和力。抑制机制是基于掩盖由coreNLS氨基酸形成的天然结合相互作用。令人惊讶的是,配体干扰由输入蛋白α氨基酸形成的结合相互作用对抑制作用的贡献很小。我们发现DP9是一种比dp90更强的抑制剂。通过对DP9和dp90相互作用的比较分析,我们确定了DP9相对“成功”的原子原因,这是由于该抑制剂嵌入在NLS赖氨酸残基的侧链之间。为了测试我们的模拟,我们进行了alphasgreen实验,测量了抑制剂的IC50值。AlphaScreen的数据证实了抑制剂的硅排名。通过结合我们最近的研究,我们讨论了扩散结合抑制剂影响蛋白质-蛋白质相互作用的假定机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ligands binding diffusively to protein target act as inhibitors of protein-protein interactions.

Nuclear localization signal (NLS) sequence from capsid protein of Venezuelan equine encephalitis virus (VEEV) binds to importin-α transport protein and clogs nuclear import. Prevention of viral NLS binding to importin-α may represent a viable therapeutic route. Here, we investigate the molecular mechanism by which two diffusively binding inhibitors, DP9 and DP9o, interfere with the binding of VEEV's NLS peptide to importin-α. Our study uses all-atom replica exchange molecular dynamics simulations, which probe the competitive binding of the VEEV NLS fragment, the coreNLS peptide, and the inhibitors to importin-α. Our previous simulations of non-competitive binding of the coreNLS, in which it natively binds to importin-α, are used as a reference. Both inhibitors abrogate native peptide binding and reduce the fraction of its native interactions, but they fail to prevent its non-native binding to importin-α. As a result, these inhibitors turn the coreNLS into diffusive binder, which adopts a manifold of non-native binding poses. Competition from the inhibitors compromises the free energy of coreNLS binding to importin-α showing that they reduce its binding affinity. The inhibition mechanism is based on masking the native binding interactions formed by the coreNLS amino acids. Surprisingly, ligand interference with the binding interactions formed by importin-α amino acids contributes little to inhibition. We show that DP9 is a stronger inhibitor than DP9o. By comparative analysis of DP9 and DP9o interactions we determine the atomistic reason for a relative "success" of DP9, which is due to the intercalation of this inhibitor between the side chains of NLS lysine residues. To test our simulations, we performed AlphaScreen experiments measuring IC50 values for the inhibitors. AlphaScreen data confirmed in silico ranking of the inhibitors. By combining our recent studies, we discuss the putative mechanism by which diffusively binding inhibitors impact protein-protein interactions.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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