Nalidixic acid inhibits the aggregation of HSA: Utilizing the molecular simulations to uncover the detailed insights

IF 2.6 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry Pub Date : 2025-02-28 DOI:10.1016/j.compbiolchem.2025.108415

Jihad Alrehaili , Razique Anwer , Faizan Abul Qais

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引用次数: 0

Abstract

Neurodegenerative diseases such as Parkinson's and Alzheimer's lead to the gradual decline of the nervous system, resulting in cognitive and motor impairments. With an aging population, the prevalence and associated healthcare costs are anticipated to rise. Misfolded protein aggregates are central to these diseases, disrupting cellular function and causing neuronal death. Preventing these toxic aggregates could preserve neurons and slow disease progression. Understanding how to inhibit protein aggregation is crucial for developing effective treatments. We explored the effect of nalidixic acid (NA) on protein aggregation using human serum albumin (HSA) as model protein. In vitro assays demonstrated that NA significantly reduced ThT fluorescence by 47.10 % and decreased turbidity by 63.07 %. NA also protected the protein’s hydrophobic surfaces. The α-helical content of HSA dropped from 56.23 % to 11.43 % but was restored to 38.53 % with NA. We then utilized advanced molecular simulations to understand the kinetics and mechanism of aggregation inhibition by NA. Binding studies showed that NA attaches to HSA’s subdomain IIA with a binding energy of −7.8 kcal/mol through hydrogen bonds, Van der Waals forces, and hydrophobic interactions. Molecular simulations confirmed the stability of HSA-NA complex. Additionally, NA increased solvent accessibility of HSA_282–292 oligomers, reduced hydrogen bonding, and prevented β-sheet formation. Compared to existing anti-aggregation strategies, NA offers a promising alternative with its potential therapeutic applications in neurodegenerative diseases by stabilizing protein structures and preventing misfolding. These findings highlight NA's potential as a candidate for inhibiting protein aggregation and offer insights for therapeutic approaches. Further experimental studies utilizing in vivo models are needed to validate the anti-aggregation potential of NA.

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萘啶酸抑制 HSA 的聚集：利用分子模拟揭示详细见解

帕金森氏症和阿尔茨海默氏症等神经退行性疾病会导致神经系统逐渐衰退，造成认知和运动障碍。随着人口老龄化的加剧，预计这种疾病的发病率和相关医疗费用都将上升。折叠错误的蛋白质聚集体是这些疾病的核心，会破坏细胞功能并导致神经元死亡。防止这些有毒的聚集体可以保护神经元并减缓疾病的进展。了解如何抑制蛋白质聚集对于开发有效的治疗方法至关重要。我们以人血清白蛋白（HSA）为模型蛋白，探讨了萘啶酸（NA）对蛋白聚集的影响。体外实验表明，NA 能显著降低 ThT 荧光 47.10%，降低浑浊度 63.07%。NA 还能保护蛋白质的疏水表面。HSA 的 α-helical 含量从 56.23% 下降到 11.43%，但在 NA 的作用下又恢复到 38.53%。随后，我们利用先进的分子模拟来了解 NA 抑制聚集的动力学和机制。结合研究表明，通过氢键、范德华力和疏水作用，NA 与 HSA 子域 IIA 的结合能为 -7.8 kcal/mol。分子模拟证实了 HSA-NA 复合物的稳定性。此外，NA 增加了 HSA282-292 低聚物的溶剂可及性，减少了氢键作用，并阻止了 β 片的形成。与现有的抗聚集策略相比，NA通过稳定蛋白质结构和防止错误折叠，为神经退行性疾病的潜在治疗应用提供了一种前景广阔的替代方案。这些发现凸显了NA作为抑制蛋白质聚集候选物质的潜力，并为治疗方法提供了启示。要验证NA的抗聚集潜力，还需要利用体内模型开展进一步的实验研究。

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来源期刊

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.