抗病毒药物利巴韦林能有效调节α-突触核蛋白的淀粉样转化

IF 2.6 4区 生物学 Q2 BIOLOGY Computational Biology and Chemistry Pub Date : 2024-07-16 DOI:10.1016/j.compbiolchem.2024.108155
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引用次数: 0

摘要

α-突触核蛋白(α-syn)是一种内在紊乱的蛋白质,在遗传学和神经病理学上与帕金森病有关,这种蛋白质会在大脑内聚集。因此,确定能够阻碍α-syn聚集的化合物是开发疾病调节疗法的一个很有前景的方法。在此,我们利用一系列生物信息学工具和生物物理技术的系统分析,研究了利巴韦林(一种美国 FDA 批准的化合物)在抑制 α-syn 淀粉样蛋白转化方面的功效。利巴韦林显示出剂量依赖性抗聚集倾向,它能有效抑制α-syn成熟纤维状聚集体的形成,即使在最低浓度下,ThT最大值也降低了69%。利巴韦林通过与 α-syn 的 NAC 结构域相互作用,避免了成熟纤维状聚集体的形成。利巴韦林通过产生具有较低交叉β片特征的低阶聚集体,重定向了α-syn的淀粉样转化,并阻止了路径上淀粉样的形成。总之,我们的研究提出了利巴韦林的新功效,它是治疗帕金森病的一种有前途的分子。
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The antiviral drug Ribavirin effectively modulates the amyloid transformation of α-Synuclein protein

α-Synuclein (α-syn) is an intrinsically disordered protein, linked genetically and neuropathologically to Parkinson's disease where this protein aggregates within the brain. Hence, identifying compounds capable of impeding α-syn aggregation puts forward a promising approach for the development of disease-modifying therapies. Herein, we investigated the efficacy of Ribavirin, an FDA-approved compound, in curtailing α-syn amyloid transformation, employing an array of bioinformatic tools and systematic analysis using biophysical techniques. Ribavirin shows a dose dependent anti-aggregation propensity where it effectively subdued the formation of mature fibrillar aggregates of α-syn, where even at the lowest concentration there was a 69 % reduction in the ThT maxima. Ribavirin averts the formation of mature fibrillar aggregates by interacting with the NAC domain of α-syn. Ribavirin redirects the amyloid transformation of α-syn by emanating aggregates of lower order with reduced cross β-sheet signature and revokes the formation of on-pathway amyloids. Collectively, our study puts forward the novel potency of Ribavirin as a promising molecule for therapeutic intervention in Parkinson’s disease.

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来源期刊
Computational Biology and Chemistry
Computational Biology and Chemistry 生物-计算机:跨学科应用
CiteScore
6.10
自引率
3.20%
发文量
142
审稿时长
24 days
期刊介绍: Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
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