Introducing dysfunctional Protein-Protein Interactome (dfPPI) – A platform for systems-level protein-protein interaction (PPI) dysfunction investigation in disease

IF 6.1 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Current opinion in structural biology Pub Date : 2024-07-13 DOI:10.1016/j.sbi.2024.102886
Souparna Chakrabarty , Shujuan Wang , Tanaya Roychowdhury , Stephen D. Ginsberg , Gabriela Chiosis
{"title":"Introducing dysfunctional Protein-Protein Interactome (dfPPI) – A platform for systems-level protein-protein interaction (PPI) dysfunction investigation in disease","authors":"Souparna Chakrabarty ,&nbsp;Shujuan Wang ,&nbsp;Tanaya Roychowdhury ,&nbsp;Stephen D. Ginsberg ,&nbsp;Gabriela Chiosis","doi":"10.1016/j.sbi.2024.102886","DOIUrl":null,"url":null,"abstract":"<div><p>Protein-protein interactions (PPIs) play a crucial role in cellular function and disease manifestation, with dysfunctions in PPI networks providing a direct link between stressors and phenotype. The dysfunctional Protein-Protein Interactome (dfPPI) platform, formerly known as epichaperomics, is a newly developed chemoproteomic method aimed at detecting dynamic changes at the systems level in PPI networks under stressor-induced cellular perturbations within disease states. This review provides an overview of dfPPIs, emphasizing the novel methodology, data analytics, and applications in disease research. dfPPI has applications in cancer research, where it identifies dysfunctions integral to maintaining malignant phenotypes and discovers strategies to enhance the efficacy of current therapies. In neurodegenerative disorders, dfPPI uncovers critical dysfunctions in cellular processes and stressor-specific vulnerabilities. Challenges, including data complexity and the potential for integration with other omics datasets are discussed. The dfPPI platform is a potent tool for dissecting disease systems biology by directly informing on dysfunctions in PPI networks and holds promise for advancing disease identification and therapeutics.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"88 ","pages":"Article 102886"},"PeriodicalIF":6.1000,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0959440X24001131/pdfft?md5=ce1626c6a05f554e967c55418222e73c&pid=1-s2.0-S0959440X24001131-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current opinion in structural biology","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0959440X24001131","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Protein-protein interactions (PPIs) play a crucial role in cellular function and disease manifestation, with dysfunctions in PPI networks providing a direct link between stressors and phenotype. The dysfunctional Protein-Protein Interactome (dfPPI) platform, formerly known as epichaperomics, is a newly developed chemoproteomic method aimed at detecting dynamic changes at the systems level in PPI networks under stressor-induced cellular perturbations within disease states. This review provides an overview of dfPPIs, emphasizing the novel methodology, data analytics, and applications in disease research. dfPPI has applications in cancer research, where it identifies dysfunctions integral to maintaining malignant phenotypes and discovers strategies to enhance the efficacy of current therapies. In neurodegenerative disorders, dfPPI uncovers critical dysfunctions in cellular processes and stressor-specific vulnerabilities. Challenges, including data complexity and the potential for integration with other omics datasets are discussed. The dfPPI platform is a potent tool for dissecting disease systems biology by directly informing on dysfunctions in PPI networks and holds promise for advancing disease identification and therapeutics.

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
引入功能障碍蛋白质-蛋白质相互作用组(dfPPI)--系统级蛋白质-蛋白质相互作用(PPI)功能障碍疾病研究平台
蛋白质-蛋白质相互作用(PPI)在细胞功能和疾病表现中起着至关重要的作用,PPI网络的功能失调是应激源与表型之间的直接联系。功能失调蛋白-蛋白相互作用组(dfPPI)平台以前被称为外显子组学,是一种新开发的化学蛋白组学方法,旨在检测疾病状态下应激物诱导的细胞扰动在 PPI 网络系统水平上的动态变化。本综述概述了 dfPPI,强调了其新颖的方法、数据分析以及在疾病研究中的应用。dfPPI 在癌症研究中得到了应用,它能识别维持恶性表型不可或缺的功能障碍,并发现提高当前疗法疗效的策略。在神经退行性疾病中,dfPPI 发现了细胞过程中的关键功能障碍和压力特异性弱点。会上讨论了所面临的挑战,包括数据的复杂性以及与其他全息数据集整合的潜力。dfPPI 平台通过直接告知 PPI 网络中的功能障碍,是剖析疾病系统生物学的有力工具,有望推动疾病识别和治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Current opinion in structural biology
Current opinion in structural biology 生物-生化与分子生物学
CiteScore
12.20
自引率
2.90%
发文量
179
审稿时长
6-12 weeks
期刊介绍: Current Opinion in Structural Biology (COSB) aims to stimulate scientifically grounded, interdisciplinary, multi-scale debate and exchange of ideas. It contains polished, concise and timely reviews and opinions, with particular emphasis on those articles published in the past two years. In addition to describing recent trends, the authors are encouraged to give their subjective opinion of the topics discussed. In COSB, we help the reader by providing in a systematic manner: 1. The views of experts on current advances in their field in a clear and readable form. 2. Evaluations of the most interesting papers, annotated by experts, from the great wealth of original publications. [...] The subject of Structural Biology is divided into twelve themed sections, each of which is reviewed once a year. Each issue contains two sections, and the amount of space devoted to each section is related to its importance. -Folding and Binding- Nucleic acids and their protein complexes- Macromolecular Machines- Theory and Simulation- Sequences and Topology- New constructs and expression of proteins- Membranes- Engineering and Design- Carbohydrate-protein interactions and glycosylation- Biophysical and molecular biological methods- Multi-protein assemblies in signalling- Catalysis and Regulation
期刊最新文献
Characterizing heterogeneity in amyloid formation processes. Biochemistry and genetics are coming together to improve our understanding of genotype to phenotype relationships Deep learning for intrinsically disordered proteins: From improved predictions to deciphering conformational ensembles Short circuit: Transcription factor addiction as a growing vulnerability in cancer Conformational penalties: New insights into nucleic acid recognition
×
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