Sardarpour Negar, Goodarzi Zahra, Gharaghani Sajjad
Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran.
Laboratory of Bioinformatics and Drug Design (LBD), Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran.
Iran J Biotechnol. 2024 Apr 1;22(2):e3718. doi: 10.30498/ijb.2024.398939.3718. eCollection 2024 Apr.
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.
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 IC 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.
The targets with the highest protein interactions, as identified by PPI analysis on cancer signaling pathways, were selected as hub proteins. Natural compounds with IC 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.
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.
本研究旨在介绍一种方法，用于鉴定含有有效天然化合物的药用植物，这些化合物具有最可能的协同效应，以多靶点方式抑制癌症的存活和增殖。
为了选择靶点，从KEGG数据库中定义了参与癌症发展的信号通路，并使用STRING软件研究了这些通路内基因的蛋白质-蛋白质相互作用（PPI）。然后将14个度最高的蛋白质鉴定为靶点。使用NPASS数据库，根据天然化合物对50种癌细胞系的IC值进行初步筛选。最后，将总共1107种天然化合物与14个选定的参与癌症的靶点以及5个参与一般药物副作用的靶点进行对接。
通过对癌症信号通路的PPI分析确定的具有最高蛋白质相互作用的靶点被选为枢纽蛋白。然后使用NPASS数据库将对癌细胞系IC值小于20000 nM的天然化合物与这些选定的靶点进行对接。如果一起使用，与选定靶点结合能低的天然化合物被鉴定为癌症进展的潜在协同抑制剂。此外，报告含有最广泛已鉴定天然化合物的植物被引入作为对抗癌症发展的潜在协同效应来源。
我们提出了一种预筛选天然化合物数据库的方法，以鉴定对癌症中多种分子机制产生协同反应可能性高的数据。然而，需要进一步的验证方法来确认它们的有效性。
