Fluorescence resonance energy transfer in revealing protein-protein interactions in living cells

被引:2
|
作者
Bhaumik, Sukesh R. [1 ]
机构
[1] Southern Illinois Univ, Sch Med, Dept Biochem & Mol Biol, Carbondale, IL 62901 USA
基金
美国国家卫生研究院;
关键词
19S PROTEASOME SUBCOMPLEX; PRE-INITIATION COMPLEX; BOX-BINDING PROTEIN; IN-VIVO TARGET; TRANSCRIPTIONAL INITIATION; ACTIVATION DOMAIN; FRET ANALYSIS; REGULATORY MECHANISMS; COMPUTATIONAL METHODS; INTERACTION NETWORKS;
D O I
10.1042/ETLS20200337
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Genes are expressed to proteins for a wide variety of fundamental biological processes at the cellular and organismal levels. However, a protein rarely functions alone, but rather acts through interactions with other proteins to maintain normal cellular and organismal functions. Therefore, it is important to analyze the protein-protein interactions to determine functional mechanisms of proteins, which can also guide to develop therapeutic targets for treatment of diseases caused by altered protein-protein interactions leading to cellular/organismal dysfunctions. There is a large number of methodologies to study protein interactions in vitro, in vivo and in silico, which led to the development of many protein interaction databases, and thus, have enriched our knowledge about protein-protein interactions and functions. However, many of these interactions were identified in vitro, but need to be verified/validated in living cells. Furthermore, it is unclear whether these interactions are direct or mediated via other proteins. Moreover, these interactions are representative of cell-and time-average, but not a single cell in real time. Therefore, it is crucial to detect direct protein-protein interactions in a single cell during biological processes in vivo, towards understanding the functional mechanisms of proteins in living cells. Importantly, a fluorescence resonance energy transfer (FRET)-based methodology has emerged as a powerful technique to decipher direct protein-protein interactions at a single cell resolution in living cells, which is briefly described in a limited available space in this mini-review.
引用
收藏
页码:49 / 59
页数:11
相关论文
共 50 条
  • [31] Predicting Protein-Protein Interactions from the Molecular to the Proteome Level
    Keskin, Ozlem
    Tuncbag, Nurcan
    Gursoy, Attila
    CHEMICAL REVIEWS, 2016, 116 (08) : 4884 - 4909
  • [32] Improving the prediction of yeast protein function using weighted protein-protein interactions
    Ahmed, Khaled S.
    Saloma, Nahed H.
    Kadah, Yasser M.
    THEORETICAL BIOLOGY AND MEDICAL MODELLING, 2011, 8
  • [33] PrePPI: a structure-informed database of protein-protein interactions
    Zhang, Qiangfeng Cliff
    Petrey, Donald
    Garzon, Jose Ignacio
    Deng, Lei
    Honig, Barry
    NUCLEIC ACIDS RESEARCH, 2013, 41 (D1) : D828 - D833
  • [34] Prediction of protein-protein interactions using symmetrical encoding scheme
    Ni, Qingshan
    Wang, Zhengzhi
    Han, Qingjuan
    Wang, Guangyun
    Zhao, Yingjie
    Li, Gangguo
    2009 3RD INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING, VOLS 1-11, 2009, : 740 - +
  • [35] A coevolution analysis for identifying protein-protein interactions by Fourier transform
    Yin, Changchuan
    Yau, Stephen S. -T.
    PLOS ONE, 2017, 12 (04):
  • [36] Quantifying protein-protein interactions in high throughput using protein domain microarrays
    Kaushansky, Alexis
    Allen, John E.
    Gordus, Andrew
    Stiffler, Michael A.
    Karp, Ethan S.
    Chang, Bryan H.
    MacBeath, Gavin
    NATURE PROTOCOLS, 2010, 5 (04) : 773 - 790
  • [37] A proximity labeling method for protein-protein interactions on cell membrane
    Li, Qiongyu
    Xie, Yixuan
    Rice, Rachel
    Maverakis, Emanual
    Lebrilla, Carlito B.
    CHEMICAL SCIENCE, 2022, 13 (20) : 6028 - 6038
  • [38] Networks of Protein-Protein Interactions: From Uncertainty to Molecular Details
    Garcia-Garcia, Javier
    Bonet, Jaume
    Guney, Emre
    Fornes, Oriol
    Planas, Joan
    Oliva, Baldo
    MOLECULAR INFORMATICS, 2012, 31 (05) : 342 - 362
  • [39] Machine-learning techniques for the prediction of protein-protein interactions
    Sarkar, Debasree
    Saha, Sudipto
    JOURNAL OF BIOSCIENCES, 2019, 44 (04)
  • [40] The origins of the evolutionary signal used to predict protein-protein interactions
    Swapna, Lakshmipuram S.
    Srinivasan, Narayanaswamy
    Robertson, David L.
    Lovell, Simon C.
    BMC EVOLUTIONARY BIOLOGY, 2012, 12