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基于计算机的天然化合物筛选,以鉴定针对 MCM7 蛋白的潜在抗癌药物。

Computational Screening of Natural Compounds for Identification of Potential Anti-Cancer Agents Targeting MCM7 Protein.

机构信息

Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, P.O. Box 61413, Abha 62529, Saudi Arabia.

College of Medicine, King Khalid University Abha, P.O. Box 61413, Abha 62529, Saudi Arabia.

出版信息

Molecules. 2021 Sep 28;26(19):5878. doi: 10.3390/molecules26195878.


DOI:10.3390/molecules26195878
PMID:34641424
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8510405/
Abstract

Minichromosome maintenance complex component 7 (MCM7) is involved in replicative licensing and the synthesis of DNA, and its overexpression is a fascinating biomarker for various cancer types. There is currently no effective agent that can prevent the development of cancer caused by the MCM7 protein. However, on the molecular level, inhibiting MCM7 lowers cancer-related cellular growth. With this purpose, this study screened 452 biogenic compounds extracted from the UEFS Natural Products dataset against MCM protein by using the in silico art of technique. The hit compounds UEFS99, UEFS137, and UEFS428 showed good binding with the MCM7 protein with binding energy values of -9.95, -8.92, and -8.71 kcal/mol, which was comparatively higher than that of the control compound ciprofloxacin (-6.50). The hit (UEFS99) with the minimum binding energy was picked for molecular dynamics (MD) simulation investigation, and it demonstrated stability at 30 ns. Computational prediction of physicochemical property evaluation revealed that these hits are non-toxic and have good drug-likeness features. It is suggested that hit compounds UEFS99, UEFS137, and UEFS428 pave the way for further bench work validation in novel inhibitor development against MCM7 to fight the cancers.

摘要

微小染色体维持复合物组件 7(MCM7)参与复制许可和 DNA 的合成,其过表达是各种癌症类型的一个令人着迷的生物标志物。目前还没有有效的药物可以预防由 MCM7 蛋白引起的癌症的发展。然而,在分子水平上,抑制 MCM7 会降低与癌症相关的细胞生长。基于此目的,本研究通过使用计算机技术筛选了来自 UEFS 天然产物数据集的 452 种生物合成化合物,以寻找针对 MCM 蛋白的化合物。候选化合物 UEFS99、UEFS137 和 UEFS428 与 MCM7 蛋白具有良好的结合能力,结合能值分别为-9.95、-8.92 和-8.71 kcal/mol,这与对照化合物环丙沙星(-6.50)相比要高。候选化合物(UEFS99)的结合能最低,被选为分子动力学(MD)模拟研究,在 30 ns 内表现出稳定性。基于理化性质的计算预测表明,这些候选化合物具有非毒性和良好的类药性特征。研究结果表明,候选化合物 UEFS99、UEFS137 和 UEFS428 为进一步开发针对 MCM7 的新型抑制剂提供了依据,以对抗癌症。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe31/8510405/1e10ec0551c0/molecules-26-05878-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe31/8510405/2db3c3f47ec5/molecules-26-05878-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe31/8510405/cfffc9d75ce4/molecules-26-05878-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe31/8510405/6a8ae12e55db/molecules-26-05878-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe31/8510405/7f70e12ce3a2/molecules-26-05878-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe31/8510405/1e10ec0551c0/molecules-26-05878-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe31/8510405/2db3c3f47ec5/molecules-26-05878-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe31/8510405/cfffc9d75ce4/molecules-26-05878-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe31/8510405/6a8ae12e55db/molecules-26-05878-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe31/8510405/7f70e12ce3a2/molecules-26-05878-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe31/8510405/1e10ec0551c0/molecules-26-05878-g005.jpg

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本文引用的文献

[1]
Pharmacoinformatics and molecular dynamics simulation-based phytochemical screening of neem plant (Azadiractha indica) against human cancer by targeting MCM7 protein.

Brief Bioinform. 2021-9-2

[2]
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Nucleic Acids Res. 2020-7-9

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Nat Prod Rep. 2020-7-1

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Front Pharmacol. 2020-1-28

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Nucleic Acids Res. 2018-7-2

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Pathol Oncol Res. 2018-4

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Oncotarget. 2017-6-6

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Sci Rep. 2017-3-3

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