新型噻唑类抗癌药物的合成与表征:分子对接与DFT研究

IF 3.1 Q2 TOXICOLOGY
R. Raveesha , A.M. Anusuya , A.V. Raghu , K. Yogesh Kumar , M.G. Dileep Kumar , S.B. Benaka Prasad , M.K. Prashanth
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引用次数: 38

摘要

以2-(3-氰基-4-异丁基苯基)-4-甲基噻唑-5-羧酸与取代苯胺反应合成了新的噻唑衍生物(2a-l)。以顺铂为阳性对照,研究了合成的噻唑衍生物对MCF-7(人乳腺癌)、MDA-MB-231(乳腺癌)、HeLa(宫颈癌)、HT-29、HCT 116(结肠癌)和正常肝癌细胞株的抗癌活性。通过细胞凋亡评估和分子对接研究其抗癌机制。以人表皮生长因子受体(HER2, PDB ID: 3RCD)为可能的抗癌靶点,利用Auto Dock进行了有效化合物的分子对接研究。ADMET结果表明,被测化合物在Lipinski的五规则内具有显著的结果。此外,利用密度泛函理论(DFT)在B3LYP/6-31G (d,p)水平上进行了计算,研究了强效化合物的电子性质。讨论了前沿分子轨道能和原子净电荷。
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 characterization of novel thiazole derivatives as potential anticancer agents: Molecular docking and DFT studies

Synthesis and characterization of novel thiazole derivatives as potential anticancer agents: Molecular docking and DFT studies

New thiazole derivatives (2a-l) were synthesized via the reaction of 2-(3-cyano-4-isobutoxyphenyl)-4-methylthiazole-5-carboxylic acid with substituted phenyl amines. The anticancer activity of the synthesized thiazole derivatives was examined against MCF-7 (human breast), MDA-MB-231 (mammary carcinomas), HeLa (Cervical cancer), HT-29, HCT 116 (Colon cancer), and normal chang liver cancer cell lines, whereas cisplatin was employed as a positive control. The anticancer mechanisms were studied via apoptosis assessments, as well as molecular docking. The molecular docking study of potent compounds was carried out against the human epidermal growth factor receptor (HER2, PDB ID: 3RCD) as a possible target for anticancer activity using Auto Dock vina. ADMET results indicated that tested compounds have significant results within the close agreement of Lipinski’s rule of five. In addition, computational work employing density functional theory (DFT) was also carried out at the B3LYP/6-31G (d,p) level to investigate the electronic properties of the potent compounds. The frontier molecular orbital energy and atomic net charges were discussed.

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来源期刊
Computational Toxicology
Computational Toxicology Computer Science-Computer Science Applications
CiteScore
5.50
自引率
0.00%
发文量
53
审稿时长
56 days
期刊介绍: Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs
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