含苯并咪唑类磺胺类似物的合成、α-葡萄糖苷酶、α-淀粉酶体外抑制电位及分子对接研究

IF 2.218 Q2 Chemistry
Hayat Ullah , Tayyaba Batool , Ayesha Nawaz , Fazal Rahim , Fahad Khan , Amjad Hussain
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引用次数: 2

摘要

我们合成了14个含苯并咪唑的磺胺类似物(1-14),并利用NMR和HR-EIMS对其进行了表征。合成的类似物对α-葡萄糖苷酶和α-淀粉酶的IC50值分别为9.20±0.10 ~ 38.30±0.40 μM (α-葡萄糖苷酶)和5.20±0.30 ~ 18.20±0.30 μM (α-淀粉酶),与对照药物阿卡波糖(IC50 = 38.45±0.80 &)相比,均表现出良好的抑制能力;11.12±0.15 μM)。α-淀粉酶抑制剂3的IC50值为5.20±0.30 μM, α-葡萄糖苷酶抑制剂6的IC50值为9.20 ~ 0.10 μM。其他类似物对α-葡萄糖苷酶表现出优异的效价,而对α-淀粉酶表现出优异至中等效价。通过建立构效关系来确定取代基在苯基环上的数量、类型、位置和给电子/吸电子作用对药效的增减作用。为了证明最有效的类似物与酶活性位点的结合相互作用,进行了分子对接研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthesis, in vitro α-glucosidase, α-amylase inhibitory potentials and molecular docking study of benzimidazole bearing sulfonamide analogues

We synthesized fourteen benzimidazole-containing sulfonamide analogs (1–14), characterized them using methods including NMR and HR-EIMS. The synthesized analogs were then tested against the enzymes α-glucosidase and α-amylase showing IC50 values ranging from 9.20 ± 0.10 to 38.30 ± 0.40 μM (for α-glucosidase) and 5.20 ± 0.30 to 18.20 ± 0.30 μM (for α-amylase), all analogues show good inhibitory capability when compared to the reference medication acarbose (IC50 = 38.45 ± 0.80 & 11.12 ± 0.15 μM, respectively). The strongest inhibitor among the series for α-amylase analogues was 3 (IC50 = 5.20±0.30 μM), whereas the strongest inhibitor in the series for α-glucosidase was analog 6 (IC50 = 9.20 0.10 μM). All other analogs showed excellent potency against the α-glucosidase enzyme while in case of α-amylase analogs showed excellent to moderate potency. The structure-activity relationship was established for determining the increase/decrease in potency due to quantity, type, position, and electron-donating/withdrawing effects of the substituent/s on the phenyl ring. To demonstrate the binding interaction of the most potent analogues with the enzyme's active sites, a molecular docking research was performed.

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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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