Synthesis, in vitro α-glucosidase, anti-bacterial, anti-fungal activities and in silico molecular docking studies of benzohydrazide derivatives

IF 2.218 Q2 Chemistry Chemical Data Collections Pub Date : 2023-09-29 DOI:10.1016/j.cdc.2023.101088
Muhammad Mujeeb Ali , Shoaib Khan , Hayat Ullah , Irfan Ahmad , Obaid Ur Rehman Abid , Rafaqat Hussain , Yousaf Khan , Khurram Shoaib , Farhan Ali , Mohammed A. Assiri
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Abstract

In the present study, various alkyl substituted moieties were synthesized (1–15) and characterized through various spectroscopic techniques such as 1HNMR, 13CNMR and HREI-MS. After confirmation, the products were then tested against fungal and bacterial strains in which almost all compounds were found with significant biological potentials. In addition, these compounds were further screened for their α-glucosidase activity in the presence of standard drug acarbose (IC50 = 8.52 ± 0.10 µM). Among the screened, few compounds shown moderate to good inhibitory potential but in this regard compound (1–3) exhibited excellent potential with inhibitory concentration of compound-1 (IC50 = 3.12 ± 0.10 µM), compound-2 (IC50 = 5.50 ± 0.20 µM) and compound-3 (IC50 = 6.20 ± 0.10 µM). Moreover, binding interaction of the most potent moieties with the active site of enzymes was determined through molecular docking study.

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苯并肼衍生物的合成、体外α-葡萄糖苷酶、抗菌、抗真菌活性及在硅分子对接研究
在本研究中,合成了不同的烷基取代基团(1-15),并通过各种光谱技术如1HNMR, 13CNMR和HREI-MS进行了表征。确认后,对产品进行真菌和细菌菌株的测试,发现几乎所有化合物都具有显著的生物潜力。在标准药物阿卡波糖(IC50 = 8.52±0.10µM)存在下,进一步筛选这些化合物的α-葡萄糖苷酶活性。在筛选的化合物中,很少有化合物表现出中等至良好的抑制电位,但化合物(1-3)表现出优异的抑制电位,化合物-1 (IC50 = 3.12±0.10µM),化合物-2 (IC50 = 5.50±0.20µM)和化合物-3 (IC50 = 6.20±0.10µM)的抑制浓度。此外,通过分子对接研究确定了最有效的部分与酶活性位点的结合相互作用。
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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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