Tp53基因与Covid - 19病毒的相关性分析

Q4 Pharmacology, Toxicology and Pharmaceutics

Current Pharmacogenomics and Personalized Medicine Pub Date : 2022-06-17 DOI:10.2174/1875692119666220617160537

L. C, K. P K

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引用次数: 0

摘要

探索对感染SARS-Cov-2的癌症患者最有效的抗癌药物。利用生物分子网络分析发现了TP53与SARS-CoV-2之间的相关性。TP53基因突变的癌症患者更容易感染SARS-Cov-2病毒，因为它是人类癌症中最常见的肿瘤抑制基因突变。本研究的主要目的是为SARS-Cov-2感染患者发现最有效和最有效的抗癌治疗方法。Topp基因分析基于分子功能、生物学过程和途径分析对候选基因进行优先排序。使用Cytoscape 2.8.2进行生物分子网络。蛋白质-蛋白质相互作用网络用于鉴定功能相关蛋白。蛋白质-药物相互作用网络用于观察药物的分子治疗效果。利用Cytohubba对网络进行进一步分析，找出枢纽节点。通过分子对接研究蛋白质-配体相互作用，通过分子动力学模拟进一步评价蛋白质-配体复合物的稳定性。通过Toppgene分析对功能相关基因进行优先排序。通过Cytohabba研究发现，UBE2N、BRCA1、BARD1、TP53、DPP4基因具有较高的程度和中心性评分。根据蛋白质-药物相互作用分析，5-氟尿嘧啶、甲氨喋呤、替莫唑胺、法比拉韦和左氧氟沙星等药物与中枢蛋白有实质性的关联。最后，一项对接研究显示，5-氟尿嘧啶与甲氨蝶呤、Favipiravir和左氧氟沙星相比，具有最高的连接值和稳定性。用于发现TP53与SARS-CoV-2之间联系的生物分子网络研究发现，5-氟尿嘧啶对TP53及其相关基因如UBE2N、BRCA1、RARD1和SARS-CoV-2特异性DPP4具有更高的亲和力。对于TP53基因突变和covid - 19感染的癌症患者，这些治疗被认为是最有效的。

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The Tp53 Gene And Covid 19 Virus: A Correlation Analysis

To discover the most effective anti-cancer medicine for cancer patients who are infected with SARS-Cov-2. The correlation between TP53 and SARS-CoV-2 was discovered using biomolecular networking analysis. Cancer patients with TP53 gene mutations are more likely to be infected with the SARS-Cov-2 virus since it is the most frequently mutated tumor suppressor gene in human cancer. The main goal of this study is to discover the most effective and efficient anti-cancer therapy for patients with SARS-Cov-2 infection. Topp gene analysis was used to prioritize candidate genes based on molecular function, biological process, and pathway analysis. Biomolecular networking was carried out using Cytoscape 2.8.2. The Protein-protein Interaction network was used to identify the functionally associated proteins. Protein-Drug Interaction network was used to observe the molecular therapeutic efficiency of drugs. The network was further analyzed using Cytohubba to find the hub nodes. The molecular docking was used to study the protein-ligand interaction and the protein-ligand complex was further evaluated through molecular dynamic simulation to determine its stability. Functionally relevant genes were prioritized through Toppgene analysis. Through Cytohabba study it was found that the genes UBE2N, BRCA1, BARD1, TP53, and DPP4 was having a high degree and centrality score. The drugs 5-fluorouracil, Methotrexate, Temozolomide, Favipiravir, and Levofloxacin have a substantial association with the hub protei, according to protein-drug interaction analysis. Finally, a docking study revealed that 5-fluorouracil have the highest connection value and stability when compared to Methotrexate, Favipiravir, and Levofloxacin. The biomolecular networking study used to discover the link between TP53 and SARS-CoV-2 found that 5-fluorouracil, had a higher affinity for binding to TP53 and its related genes, such as UBE2N, BRCA1, RARD1, and SARS-CoV-2 specific DPP4. For cancer patients with TP53 gene mutations and covid 19 infection, these treatments were determined to be the most effective.

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来源期刊

Current Pharmacogenomics and Personalized Medicine Pharmacology, Toxicology and Pharmaceutics-Pharmacology

CiteScore

0.40

自引率

0.00%

发文量

期刊介绍： Current Pharmacogenomics and Personalized Medicine (Formerly ‘Current Pharmacogenomics’) Current Pharmacogenomics and Personalized Medicine (CPPM) is an international peer reviewed biomedical journal that publishes expert reviews, and state of the art analyses on all aspects of pharmacogenomics and personalized medicine under a single cover. The CPPM addresses the complex transdisciplinary challenges and promises emerging from the fusion of knowledge domains in therapeutics and diagnostics (i.e., theragnostics). The journal bears in mind the increasingly globalized nature of health research and services.