Au(III)卟啉复合物对MCF-7人乳腺癌的结构-生物抑制活性的计算研究

IF 2.218 Q2 Chemistry
Marwa Alaqarbeh , Larbi El Mchichi , Amr S. Abouzied , Si Mohamed Bouzzine , Bader Huwaimel , Mohammed Bouachrine
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引用次数: 0

摘要

不同的方法和药物方案用于治疗各种类型的癌症,因为有机分子主要用于抗癌治疗。由于其作为抗癌药物的显著效果,金属基化合物被用来代替有机分子作为抗癌药物。本研究采用计算方法DFT、分子对接、分子动力学模拟等分析Au(III)卟啉复合物与MCF-7人乳腺癌细胞靶蛋白相互作用的稳定性。结果表明,Au(III)卟啉复合物对三种受体2JFR、3HB5和4YTO的亲和力优于蛋白3ERT。金原子(Au)的疏水相互作用增加了它们与受体的结合亲和力。因此,这些结果为Au(III)卟啉复合物作为一种有效的乳腺癌抑制剂提供了有益的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Computational investigation of structural-biological inhibitory activity for Au(III) porphyrin complexes against MCF-7 human breast cancer

Computational investigation of structural-biological inhibitory activity for Au(III) porphyrin complexes against MCF-7 human breast cancer

Different methods and medication protocols were used to treat various cancer types, as organic molecules were used mainly as anticancer therapies. Due to their remarkable results as anticancer drugs, promising metal-based compounds were used instead of organic molecules as anticancer drugs. This study used computational methods DFT, molecular docking, and molecular dynamics simulation to analyze the stability of interactions between Au(III) porphyrin complexes and the target protein of MCF-7 human breast cancer cells. The results show that Au(III) porphyrin complexes have better affinity to the three receptors 2JFR, 3HB5, and 4YTO than the protein 3ERT. The gold atom (Au) hydrophobic interaction increased their binding affinity to the receptor. Therefore, the results have provided helpful information on the Au(III) porphyrin complexes as a potent inhibitor against breast cancer.

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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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