Docking-Based Virtual Screening Method for Selecting Natural Compounds with Synergistic Inhibitory Effects Against Cancer Signalling Pathways Using a Multi-Target Approach.

IF 1.6 4区 生物学 Q4 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Negar Sardarpour, Zahra Goodarzi, Sajjad Gharaghani
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引用次数: 0

Abstract

Objectives: This study aims to introduce a methodology for identifying medicinal plants that contain effective natural compounds with the most possible synergistic effects to inhibit cancer survival and proliferation in a multi-targeted manner.

Materials and methods: To select targets, the signaling pathways involved in cancer development were defined from the KEGG database, and the protein-protein interactions (PPIs) of genes within these pathways were investigated using the STRING software. Then 14 proteins with the highest degree were identified as targets. Using the NPASS database, natural compounds were initially filtered based on their IC50 against 50 cancer cell lines. Finally, a total of 1,107 natural compounds were docked to the 14 selected targets involved in cancer and 5 targets involved in general drug side effects.

Results: The targets with the highest protein interactions, as identified by PPI analysis on cancer signaling pathways, were selected as hub proteins. Natural compounds with IC50 less than 20000 nM against cancer cell lines were then docked to these selected targets using the NPASS database. Natural compounds with low binding energy to the selected targets were identified as potential synergistic inhibitors of cancer progression if used together. Additionally, plants reported with the widest range of identified natural compounds were introduced as potential sources of synergistic effects against cancer development.

Conclusions: We have proposed a methodology for pre-screening the natural compounds database to identify potential compounds with a high likelihood of producing a synergistic response against multiple molecular mechanisms in cancer. However, further validation methods are necessary to confirm their effectiveness.

基于对接的虚拟筛选方法,利用多靶点方法选择对癌症信号通路具有协同抑制作用的天然化合物
研究目的本研究旨在介绍一种方法,用于识别含有有效天然化合物的药用植物,这些化合物具有最大可能的协同效应,能以多靶点方式抑制癌症的存活和增殖:为了选择靶点,我们从 KEGG 数据库中定义了癌症发生发展的信号通路,并使用 STRING 软件研究了这些通路中基因的蛋白-蛋白相互作用(PPIs)。然后确定了 14 个互作程度最高的蛋白质作为靶标。利用 NPASS 数据库,根据天然化合物对 50 种癌症细胞系的 IC50 值对其进行初步筛选。最后,共有 1,107 种天然化合物与 14 个选定的癌症靶点和 5 个涉及一般药物副作用的靶点进行了对接:结果:通过对癌症信号通路的 PPI 分析发现,蛋白质相互作用最高的靶点被选为枢纽蛋白。然后利用 NPASS 数据库将对癌细胞株的 IC50 小于 20000 nM 的天然化合物与这些选定的靶点对接。与所选靶点结合能量较低的天然化合物被确定为癌症进展的潜在协同抑制剂(如果同时使用)。此外,报告中还介绍了具有最广泛鉴定天然化合物的植物,它们是抗癌协同作用的潜在来源:我们提出了一种预筛选天然化合物数据库的方法,以确定极有可能对多种癌症分子机制产生协同反应的潜在化合物。然而,还需要进一步的验证方法来确认其有效性。
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来源期刊
Iranian Journal of Biotechnology
Iranian Journal of Biotechnology BIOTECHNOLOGY & APPLIED MICROBIOLOGY-
CiteScore
2.60
自引率
7.70%
发文量
20
期刊介绍: Iranian Journal of Biotechnology (IJB) is published quarterly by the National Institute of Genetic Engineering and Biotechnology. IJB publishes original scientific research papers in the broad area of Biotechnology such as, Agriculture, Animal and Marine Sciences, Basic Sciences, Bioinformatics, Biosafety and Bioethics, Environment, Industry and Mining and Medical Sciences.
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