Protein-protein interactions in a crowded environment

被引:42
作者
Bhattacharya A. [1 ]
Kim Y.C. [2 ]
Mittal J. [1 ]
机构
[1] Department of Chemical Engineering, Lehigh University, Bethlehem, PA
[2] Center for Computational Materials Science, Naval Research Laboratory, Washington DC
关键词
Cellular environment; Crowding theories; Dilute solution; Macromolecular crowding; Protein-crowder interactions; Protein-protein interactions;
D O I
10.1007/s12551-013-0111-5
中图分类号
学科分类号
摘要
Protein-protein interactions are important in many essential biological functions, such as transcription, translation, and signal transduction. Much progress has been made in understanding protein-protein association in dilute solution via experimentation and simulation. Cells, however, contain various macromolecules, such as DNA, RNA, proteins, among many others, and a myriad of non-specific interactions (usually weak) are present between these cellular constituents. In this review article, we describe the important developments in recent years that have furthered our understanding and even allowed prediction of the consequences of macromolecular crowding on protein-protein interactions. We outline the development of our crowding theory that can predict the change in binding free energy due to crowding quantitatively for both repulsive and attractive protein-crowder interactions. One of the most important findings from our recent work is that weak attractive interactions between crowders and proteins can actually destabilize protein complex formation as opposed to the commonly assumed stabilizing effect predicted based on traditional crowding theories that only account for the entropic-excluded volume effects. We also discuss the implications of macromolecular crowding on the population of encounter versus specific native complex. © 2013 International Union for Pure and Applied Biophysics (IUPAB) and Springer-Verlag Berlin Heidelberg.
引用
收藏
页码:99 / 108
页数:9
相关论文
共 50 条
[21]   Prediction of Protein-Protein Interactions Based on Protein-Protein Correlation Using Least Squares Regression [J].
Huang, De-Shuang ;
Zhang, Lei ;
Han, Kyungsook ;
Deng, Suping ;
Yang, Kai ;
Zhang, Hongbo .
CURRENT PROTEIN & PEPTIDE SCIENCE, 2014, 15 (06) :553-560
[22]   Mapping protein-protein interactions with combinatorial peptides [J].
Brian, BK .
COMPARATIVE AND FUNCTIONAL GENOMICS, 2001, 2 (05) :304-306
[23]   Study of Protein-protein Interactions in Autophagy Research [J].
Erbil-Bilir, Secil ;
Kocaturk, Nur M. ;
Yayli, Melih ;
Gozuacik, Devrim .
JOVE-JOURNAL OF VISUALIZED EXPERIMENTS, 2017, (127)
[24]   A Microfluidic Platform for Characterization of Protein-Protein Interactions [J].
Javanmard, Mehdi ;
Talasaz, Amirali H. ;
Nemat-Gorgani, Mohsen ;
Huber, David E. ;
Pease, Fabian ;
Ronaghi, Mostafa ;
Davis, Ronald W. .
IEEE SENSORS JOURNAL, 2009, 9 (08) :883-891
[25]   Exploring protein-protein interactions with phage display [J].
Sidhu, SS ;
Fairbrother, WJ ;
Deshayes, K .
CHEMBIOCHEM, 2003, 4 (01) :14-25
[26]   Imaging protein-protein interactions in living cells [J].
Hink, MA ;
Bisseling, T ;
Visser, AJWG .
PLANT MOLECULAR BIOLOGY, 2002, 50 (06) :871-883
[27]   Technologies for the identification and validation of protein-protein interactions [J].
Pichlerova, Karoline ;
Hanes, Jozef .
GENERAL PHYSIOLOGY AND BIOPHYSICS, 2021, 40 (06) :495-522
[28]   Protein-protein interactions as determinants of operon architecture [J].
Bedi, Silky ;
Rose, S. M. ;
Kaur, Simerpreet ;
Negi, Preeti ;
Sinha, Sharmistha .
BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS, 2025, 1869 (06)
[29]   Using Aptamers to Study Protein-Protein Interactions [J].
Parekh, Parag ;
Martin, Jennifer ;
Chen, Yan ;
Colon, Datia ;
Wang, Hui ;
Tan, Weihong .
PROTEIN - PROTEIN INTERACTION, 2008, 110 :177-194
[30]   The evolution network model of the protein-protein interactions [J].
Zhou, Hongwei .
PROCEEDINGS OF FIRST INTERNATIONAL CONFERENCE OF MODELLING AND SIMULATION, VOL III: MODELLING AND SIMULATION IN ELECTRONICS, COMPUTING, AND BIO-MEDICINE, 2008, :358-362