作为抗癌剂的苯并噻唑-喹啉-吡唑磺酰胺衍生物的设计、合成和生物学评价

IF 2.218 Q2 Chemistry Chemical Data Collections Pub Date : 2024-06-01 DOI:10.1016/j.cdc.2024.101136
Perugu Edukondalu , Reddymasu Sireesha , Pushpalatha Kavuluri , Paila Suresh , Gadupudi Purna Chandra Rao , Choragudi Chandrasekhar , Rudraraju Ramesh Raju
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引用次数: 0

摘要

设计并合成了一个新的苯并噻唑-喹啉-吡唑磺酰胺衍生物库(11a-j),并通过 1HNMR、13CNMR 和质谱数据确认了它们的化学结构。此外,利用 MTT 法评估了所有衍生物对四种人类癌细胞系(如前列腺癌细胞(PC3)、肺癌细胞(A549)、乳腺癌细胞(MCF-7)和前列腺癌细胞(DU-145))的初步抗癌应用,所得结果以 IC50 µM 表示。以依托泊苷为阳性对照,大多数筛选出的化合物都显示出中等至良好的活性。其中,11a、11b、11 h、11i 和 11j 五种化合物具有更强的活性。
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Design, synthesis and biological evaluation of sulfonamide derivatives of Benzothiazol-Quinoline-Pyrazoles as anticancer agents

A new library of sulfonamide derivatives of benzothiazol-quinoline-pyrazole (11a-j) were design and synthesized and their chemical structures were confirmed by 1HNMR, 13CNMR and mass spectral data. Further, all derivatives were evaluated for their preliminary anticancer applications against a panel of four human cancer cell lines such as prostate cancer cell (PC3), lung cancer cell (A549), breast cancer cell (MCF-7) and prostate cancer cell (DU-145) by using of MTT method and the obtained results were expressed with IC50 µM. Most of the screened compounds were displayed moderate to good activity and etoposide utilized as positive control. Among them, five compounds 11a, 11b, 11 h, 11i and 11j were revealed more potent activities.

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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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