作为潜在乙酰胆碱酯酶和丁酰胆碱酯酶抑制剂的噻吩硫脲衍生物的合成与分子对接研究

IF 2.218 Q2 Chemistry
Hayat Ullah , Maria Bashir , Fahad Khan , Iram Iqbal , Aroosa Iqbal , Fazal Rahim
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引用次数: 0

摘要

通过 13CNMR、1HNMR 和 HR-EIMS 合成并表征了一系列新的含噻吩的硫脲衍生物(1-11)。对合成的衍生物进行了乙酰胆碱酯酶和丁酰胆碱酯酶抑制潜力的筛选。与标准药物多奈哌齐(IC50 = 2.16 ± 0.12 µM 和 4.5 ± 0.11 µM)相比,所有衍生物都显示出不同程度的抑制潜能,对乙酰胆碱酯酶的抑制潜能为 0.40 ± 0.05 至 26.40 ± 0.40 µM,对丁酰胆碱酯酶的抑制潜能为 1.80 ± 0.10 至 36.80 ± 0.90 µM。在这两种情况下,系列类似物 3、5、7、9 和 10 的活性都比标准药物多奈哌齐高出许多倍。所有新合成的化合物都建立了结构-活性关系,主要是基于苯环上的取代模式。通过分子对接研究,证实了最具活性的衍生物与酶活性位点的结合相互作用。为了评估蛋白质配体复合物的稳定性,进行了 10ns MD 模拟。在 10ns 模拟过程中,化合物 3 等最有效的化合物显示出极高的稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthesis and molecular docking study of thiophene-bearing thiourea derivatives as potential acetylcholinesterase, and butyrylcholinesterase inhibitors

A new series of thiophene-bearing thiourea derivatives (1–11) were synthesized and characterized through 13C NMR, 1H NMR and HR-EIMS. The synthesized derivatives were screened against acetylcholinesterase, and butyrylcholinesterase inhibitory potentials. All derivatives display a variable degree of inhibitory potential ranging from 0.40 ± 0.05 to 26.40 ± 0.40 µM (against AChE) and 1.80 ± 0.10 to 36.80 ± 0.90 µM (against BuChE) as compared to standard drug donepezil (IC50 = 2.16 ± 0.12 µM and 4.5 ± 0.11 µM, respectively). In both cases, among the series analogues 3, 5, 7, 9, and 10 showed many folds better activity than standard drug donepezil. Structure-activity relationship has been also established for all newly synthesized compounds, mainly based on substitution patterns on the phenyl ring. The binding interaction of the most active derivatives with the active site of enzymes was confirmed through a molecular docking study. To evaluate the stability of the protein-ligand complexes 10 ns MD simulation was carried out. The most potent compound such as compound 3 revealed great stability during the 10 ns simulation.

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来源期刊
Chemical Data Collections
Chemical Data Collections Chemistry-Chemistry (all)
CiteScore
6.10
自引率
0.00%
发文量
169
审稿时长
24 days
期刊介绍: Chemical Data Collections (CDC) provides a publication outlet for the increasing need to make research material and data easy to share and re-use. Publication of research data with CDC will allow scientists to: -Make their data easy to find and access -Benefit from the fast publication process -Contribute to proper data citation and attribution -Publish their intermediate and null/negative results -Receive recognition for the work that does not fit traditional article format. The research data will be published as ''data articles'' that support fast and easy submission and quick peer-review processes. Data articles introduced by CDC are short self-contained publications about research materials and data. They must provide the scientific context of the described work and contain the following elements: a title, list of authors (plus affiliations), abstract, keywords, graphical abstract, metadata table, main text and at least three references. The journal welcomes submissions focusing on (but not limited to) the following categories of research output: spectral data, syntheses, crystallographic data, computational simulations, molecular dynamics and models, physicochemical data, etc.
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