Network Analysis of Anti-inflammatory Phytochemicals and Omics Data for Rheumatoid Arthritis.

IF 1.5 4区 医学 Q4 CHEMISTRY, MEDICINAL Current computer-aided drug design Pub Date : 2023-01-01 DOI:10.2174/1573409919666230106125058
Bharathi Nathan, Archana Prabahar, Sudheer Mohammed
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Abstract

Background: Rheumatoid arthritis (RA) is an inflammatory autoimmune disease that affects the synovial joints. Nearly 1.6 billion patients are affected by RA worldwide and the incidence of RA is about 0.5 to 1%. Recent studies reveal that immune cell responses and secretion of inflammatory factors are important for the control of RA.

Methods: In this study, a set of 402 phytochemicals with anti-inflammatory properties and 16 target proteins related to anti-inflammatory diseases were identified from the literature and they were subjected to network analysis. The protein-protein interaction (PPI) network was constructed using STRING (Search Tool for the Retrieval of Interacting Genes database) database. Visualization of the target gene-phytochemical network and its protein-protein interaction network was conducted using Cytoscape and further analyzed using MCODE (Molecular Complex Detection). The gene ontology and KEGG pathway analysis was performed using DAVID tool.

Results: Our results from the network approach indicate that the phytochemicals such as Withanolide, Diosgenin, and Butulin could act as potential substitute for anti-inflammatory drugs, including DMARDs. Genes such as Mitogen-activated protein kinase (MAPK) and Interleukin were found as hub genes and acted as best inhibitors for the target protein pathways. Curcumin, Catechin was also found to be involved in various signaling pathways such as NF-kappa B signaling pathway, ErbB signaling pathway and acted as the best inhibitor along with other candidate phytochemicals.

Conclusion: In the current study, we were able to identify Withanolide, Diosgenin, and Butulin as potential anti-inflammatory phytochemicals and determine their association with key pathways involved in RA through network analysis. We hypothesized that natural compounds could significantly contribute to the reduction of dosage, improve the treatment and act as a therapeutic agent for more economical and safer treatment of RA.

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类风湿关节炎抗炎植物化学物质的网络分析和组学数据。
背景:类风湿性关节炎(RA)是一种影响滑膜关节的炎症性自身免疫性疾病。全世界有近16亿RA患者,RA发病率约为0.5 - 1%。近年来的研究表明,免疫细胞反应和炎症因子的分泌对RA的控制起着重要的作用。方法:本研究从文献中鉴定出402种具有抗炎特性的植物化学物质和16种与抗炎疾病相关的靶蛋白,并对其进行网络分析。利用STRING (Search Tool for Retrieval of Interacting Genes database)数据库构建蛋白质-蛋白质相互作用(PPI)网络。利用Cytoscape对目标基因-植物化学网络及其蛋白-蛋白相互作用网络进行可视化,并利用MCODE (Molecular Complex Detection)进一步分析。使用DAVID工具进行基因本体和KEGG通路分析。结果:我们的网络方法结果表明,植物化学物质如Withanolide,薯蓣皂苷元和Butulin可以作为抗炎药物的潜在替代品,包括DMARDs。有丝裂原活化蛋白激酶(MAPK)和白介素等基因被发现是枢纽基因,是靶蛋白途径的最佳抑制剂。姜黄素、儿茶素还参与nf - κ B信号通路、ErbB信号通路等多种信号通路,并与其他候选植物化学物质一起发挥最佳抑制作用。结论:在目前的研究中,我们能够通过网络分析确定Withanolide,薯蓣皂苷元和Butulin作为潜在的抗炎植物化学物质,并确定它们与RA关键通路的关联。我们假设天然化合物可以显著减少剂量,改善治疗,并作为一种更经济、更安全的治疗RA的药物。
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来源期刊
Current computer-aided drug design
Current computer-aided drug design 医学-计算机:跨学科应用
CiteScore
3.70
自引率
5.90%
发文量
46
审稿时长
>12 weeks
期刊介绍: Aims & Scope Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews, original research articles and letter articles written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, theoretical chemistry; computational chemistry; computer and molecular graphics; molecular modeling; protein engineering; drug design; expert systems; general structure-property relationships; molecular dynamics; chemical database development and usage etc., providing excellent rationales for drug development.
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