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In silico strategies to identify protein–protein interaction modulator in cell-to-cell transmission of SARS CoV2
Transboundary and Emerging Diseases ( IF 4.3 ) Pub Date : 2022-11-15 , DOI: 10.1111/tbed.14760
Anamika Basu 1 , Anasua Sarkar 2 , Sanghamitra Bandyopadhyay 3 , Ujjwal Maulik 2
Affiliation  

RNA sequence data from SARS CoV2 patients helps to construct a gene network related to this disease. A detailed analysis of the human host response to SARS CoV2 with expression profiling by high-throughput sequencing has been accomplished with primary human lung epithelial cell lines. Using this data, the clustered gene annotation and gene network construction are performed with the help of the String database. Among the four clusters identified, only 1 with 44 genes could be annotated. Interestingly, this corresponded to basal cells with p = 1.37e − 05, which is relevant for respiratory tract infection. Functional enrichment analysis of genes present in the gene network has been completed using the String database and the Network Analyst tool. Among three types of cell–cell communication, only the anchoring junction between the basal cell membrane and the basal lamina in the host cell is involved in the virus transmission. In this junction point, a hemidesmosome structure plays a vital role in virus spread from one cell to basal lamina in the respiratory tract. In this protein complex structure, different integrin protein molecules of the host cell are used to promote the spread of virus infection into the extracellular matrix. So, small molecular blockers of different anchoring junction proteins, such as integrin alpha 3, integrin beta 1, can provide efficient protection against this deadly viral disease. ORF8 from SARS CoV2 virus can interact with both integrin proteins of human host. By using molecular docking technique, a ternary complex of these three proteins is modelled. Several oligopeptides are predicted as modulators for this ternary complex. In silico analysis of these modulators is very important to develop novel therapeutics for the treatment of SARS CoV2.

中文翻译:

在 SARS CoV2 细胞间传播中识别蛋白质-蛋白质相互作用调节剂的计算机策略

来自 SARS CoV2 患者的 RNA 序列数据有助于构建与该疾病相关的基因网络。通过高通量测序对人类宿主对 SARS CoV2 的反应进行了详细分析,并使用原代人肺上皮细胞系完成了表达谱分析。使用此数据,在 String 数据库的帮助下执行聚类基因注释和基因网络构建。在确定的四个簇中,只有 1 个具有 44 个基因可以被注释。有趣的是,这对应于具有p = 1.37e − 05,与呼吸道感染有关。使用 String 数据库和 Network Analyst 工具完成了基因网络中存在的基因的功能富集分析。在三种类型的细胞间通讯中,只有宿主细胞基底细胞膜和基底层之间的锚定连接参与病毒传播。在这个连接点,半桥粒结构在病毒从一个细胞传播到呼吸道基底层的过程中起着至关重要的作用。在这种蛋白质复合结构中,宿主细胞的不同整合素蛋白分子被用来促进病毒感染扩散到细胞外基质中。因此,不同锚定连接蛋白的小分子阻断剂,如整合素α3、整合素β1、可以针对这种致命的病毒性疾病提供有效的保护。来自 SARS CoV2 病毒的 ORF8 可以与人类宿主的两种整合素蛋白相互作用。通过使用分子对接技术,对这三种蛋白质的三元复合物进行建模。几种寡肽被预测为该三元复合物的调节剂。这些调节剂的计算机分析对于开发治疗 SARS CoV2 的新疗法非常重要。
更新日期:2022-11-15
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