甲型流感与小鼠蛋白相互作用结构域的病毒网络。

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Frontiers in bioinformatics Pub Date : 2023-02-17 eCollection Date: 2023-01-01 DOI:10.3389/fbinf.2023.1123993
Teng Ann Ng, Shamima Rashid, Chee Keong Kwoh
{"title":"甲型流感与小鼠蛋白相互作用结构域的病毒网络。","authors":"Teng Ann Ng, Shamima Rashid, Chee Keong Kwoh","doi":"10.3389/fbinf.2023.1123993","DOIUrl":null,"url":null,"abstract":"<p><p>There exist several databases that provide virus-host protein interactions. While most provide curated records of interacting virus-host protein pairs, information on the strain-specific virulence factors or protein domains involved, is lacking. Some databases offer incomplete coverage of influenza strains because of the need to sift through vast amounts of literature (including those of major viruses including HIV and Dengue, besides others). None have offered complete, strain specific protein-protein interaction records for the influenza A group of viruses. In this paper, we present a comprehensive network of predicted domain-domain interaction(s) (DDI) between influenza A virus (IAV) and mouse host proteins, that will allow the systematic study of disease factors by taking the virulence information (lethal dose) into account. From a previously published dataset of lethal dose studies of IAV infection in mice, we constructed an interacting domain network of mouse and viral protein domains as nodes with weighted edges. The edges were scored with the Domain Interaction Statistical Potential (DISPOT) to indicate putative DDI. The virulence network can be easily navigated <i>via</i> a web browser, with the associated virulence information (LD<sub>50</sub> values) prominently displayed. The network will aid influenza A disease modeling by providing strain-specific virulence levels with interacting protein domains. It can possibly contribute to computational methods for uncovering influenza infection mechanisms mediated through protein domain interactions between viral and host proteins. It is available at https://iav-ppi.onrender.com/home.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"3 ","pages":"1123993"},"PeriodicalIF":2.8000,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9982101/pdf/","citationCount":"0","resultStr":"{\"title\":\"Virulence network of interacting domains of influenza a and mouse proteins.\",\"authors\":\"Teng Ann Ng, Shamima Rashid, Chee Keong Kwoh\",\"doi\":\"10.3389/fbinf.2023.1123993\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>There exist several databases that provide virus-host protein interactions. While most provide curated records of interacting virus-host protein pairs, information on the strain-specific virulence factors or protein domains involved, is lacking. Some databases offer incomplete coverage of influenza strains because of the need to sift through vast amounts of literature (including those of major viruses including HIV and Dengue, besides others). None have offered complete, strain specific protein-protein interaction records for the influenza A group of viruses. In this paper, we present a comprehensive network of predicted domain-domain interaction(s) (DDI) between influenza A virus (IAV) and mouse host proteins, that will allow the systematic study of disease factors by taking the virulence information (lethal dose) into account. From a previously published dataset of lethal dose studies of IAV infection in mice, we constructed an interacting domain network of mouse and viral protein domains as nodes with weighted edges. The edges were scored with the Domain Interaction Statistical Potential (DISPOT) to indicate putative DDI. The virulence network can be easily navigated <i>via</i> a web browser, with the associated virulence information (LD<sub>50</sub> values) prominently displayed. The network will aid influenza A disease modeling by providing strain-specific virulence levels with interacting protein domains. It can possibly contribute to computational methods for uncovering influenza infection mechanisms mediated through protein domain interactions between viral and host proteins. It is available at https://iav-ppi.onrender.com/home.</p>\",\"PeriodicalId\":73066,\"journal\":{\"name\":\"Frontiers in bioinformatics\",\"volume\":\"3 \",\"pages\":\"1123993\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2023-02-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9982101/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3389/fbinf.2023.1123993\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fbinf.2023.1123993","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

有几个数据库提供病毒-宿主蛋白相互作用的信息。虽然大多数数据库都提供了病毒-宿主蛋白相互作用对的整理记录,但缺乏有关毒株特异性毒力因子或相关蛋白结构域的信息。由于需要筛选大量文献(包括艾滋病毒和登革热等主要病毒的文献),一些数据库提供的流感病毒株信息并不完整。目前还没有一个数据库提供完整的、针对甲型流感病毒群的特定毒株蛋白质-蛋白质相互作用记录。在本文中,我们介绍了甲型流感病毒(IAV)与小鼠宿主蛋白质之间的全面的预测域-域相互作用(DDI)网络,通过考虑毒力信息(致死剂量),可以对疾病因素进行系统研究。根据先前发表的小鼠感染 IAV 致命剂量研究数据集,我们构建了一个以小鼠和病毒蛋白质结构域为节点、带有加权边的相互作用结构域网络。用域相互作用统计势能(DISPOT)对边缘进行评分,以显示推定的DDI。该毒力网络可通过网络浏览器轻松浏览,并显著显示相关毒力信息(LD50 值)。该网络通过提供菌株特异性毒力水平和相互作用的蛋白质结构域,将有助于甲型流感疾病模型的建立。它还可能有助于采用计算方法,揭示通过病毒和宿主蛋白之间的蛋白结构域相互作用介导的流感感染机制。可在 https://iav-ppi.onrender.com/home 上查阅。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Virulence network of interacting domains of influenza a and mouse proteins.

There exist several databases that provide virus-host protein interactions. While most provide curated records of interacting virus-host protein pairs, information on the strain-specific virulence factors or protein domains involved, is lacking. Some databases offer incomplete coverage of influenza strains because of the need to sift through vast amounts of literature (including those of major viruses including HIV and Dengue, besides others). None have offered complete, strain specific protein-protein interaction records for the influenza A group of viruses. In this paper, we present a comprehensive network of predicted domain-domain interaction(s) (DDI) between influenza A virus (IAV) and mouse host proteins, that will allow the systematic study of disease factors by taking the virulence information (lethal dose) into account. From a previously published dataset of lethal dose studies of IAV infection in mice, we constructed an interacting domain network of mouse and viral protein domains as nodes with weighted edges. The edges were scored with the Domain Interaction Statistical Potential (DISPOT) to indicate putative DDI. The virulence network can be easily navigated via a web browser, with the associated virulence information (LD50 values) prominently displayed. The network will aid influenza A disease modeling by providing strain-specific virulence levels with interacting protein domains. It can possibly contribute to computational methods for uncovering influenza infection mechanisms mediated through protein domain interactions between viral and host proteins. It is available at https://iav-ppi.onrender.com/home.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
2.60
自引率
0.00%
发文量
0
期刊最新文献
Quantification of muscle fiber malformations using edge detection to investigate chronic muscle pressure ulcers. Computational identification and characterization of chitinase 1 and chitinase 2 from neotropical isolates of Beauveria bassiana. DCMA: faster protein backbone dihedral angle prediction using a dilated convolutional attention-based neural network. Identification of novel drug targets for Helicobacter pylori: structure-based virtual screening of potential inhibitors against DAH7PS protein involved in the shikimate pathway. Editorial: Women in bioinformatics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1