Oh Ki-Kwang, Adnan Md, Cho Dong-Ha
Department of Bio-Health Convergence, College of Biomedical Science, Kangwon National University, Chuncheon 24341, Korea.
Curr Issues Mol Biol. 2022 May 18;44(5):2257-2274. doi: 10.3390/cimb44050153.
In the present study, a subject of atopic dermatitis (AD) is exposed progressively to allergic rhinitis (AR) and asthma (AS), which is defined as atopic march (AM). However, both the targets and compounds against AM are still largely unknown. Hence, we investigated the overlapping targets related directly to the occurrence and development of AD, AR, and AS through public databases (DisGeNET, and OMIM). The final overlapping targets were considered as key targets of AM, which were visualized by a Venn diagram. The protein-protein interaction (PPI) network was constructed using R package software. We retrieved the association between targets and ligands via scientific journals, and the ligands were filtered by physicochemical properties. Lastly, we performed a molecular docking test (MDT) to identify the significant ligand on each target. A total of 229 overlapping targets were considered as AM causal elements, and 210 out of them were interconnected with each other. We adopted 65 targets representing the top 30% highest in degree centrality among 210 targets. Then, we obtained 20 targets representing the top 30% greatest in betweenness centrality among 65 targets. The network analysis unveiled key targets against AM, and the MDT confirmed the affinity between significant compounds and targets. In this study, we described the significance of the eight uppermost targets (CCL2, CTLA4, CXCL8, ICAM1, IL10, IL17A, IL1B, and IL2) and eight ligands (Bindarit, CTLA-4 inhibitor, Danirixin, A-205804, AX-24 HCl, Y-320, T-5224, and Apilimod) against AM, providing a scientific basis for further experiments.
在本研究中，特应性皮炎（AD）患者会逐渐发展为过敏性鼻炎（AR）和哮喘（AS），这被定义为特应性进程（AM）。然而，针对AM的靶点和化合物在很大程度上仍然未知。因此，我们通过公共数据库（DisGeNET和OMIM）研究了与AD、AR和AS的发生发展直接相关的重叠靶点。最终的重叠靶点被视为AM的关键靶点，并用维恩图进行可视化展示。使用R包软件构建蛋白质-蛋白质相互作用（PPI）网络。我们通过科学期刊检索靶点与配体之间的关联，并根据理化性质对配体进行筛选。最后，我们进行了分子对接试验（MDT），以确定每个靶点上的显著配体。共有229个重叠靶点被视为AM的致病因素，其中210个相互连接。我们选取了65个靶点，它们在210个靶点中度数中心性排名前30%。然后，我们在65个靶点中获得了20个中介中心性排名前30%的靶点。网络分析揭示了针对AM的关键靶点，MDT证实了显著化合物与靶点之间的亲和力。在本研究中，我们描述了针对AM的八个最重要的靶点（CCL2、CTLA4、CXCL8、ICAM1、IL10、IL17A、IL1B和IL2）和八个配体（Bindarit、CTLA-4抑制剂、Danirixin、A-205804、AX-24 HCl、Y-320、T-5224和Apilimod）的意义，为进一步实验提供了科学依据。
