Experimental and computational approaches for the study of calmodulin interactions

被引:36
|
作者
Reddy, A. S. N. [1 ]
Ben-Hur, Asa [2 ]
Day, Irene S. [1 ]
机构
[1] Colorado State Univ, Dept Biol, Program Mol Plant Biol, Program Cell & Mol Biol, Ft Collins, CO 80523 USA
[2] Colorado State Univ, Dept Comp Sci, Ft Collins, CO 80523 USA
基金
美国国家科学基金会;
关键词
Arabidopsis; Calcium; Ca2+ sensors; Calmodulin; CaM-binding proteins; Signaling; Bioinformatics; Interaction prediction; Protein-protein interactions; Proteome; Protein chip; PROTEIN-PROTEIN INTERACTIONS; KINESIN-LIKE PROTEIN; BINDING-PROTEIN; ARABIDOPSIS-THALIANA; GLUTAMATE-DECARBOXYLASE; CA2+/CALMODULIN-BINDING PROTEINS; INTERACTION DATABASE; BIOLOGICAL NETWORKS; SIGNALING PATHWAYS; PLASMA-MEMBRANE;
D O I
10.1016/j.phytochem.2010.12.022
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
Ca2+, a universal messenger in eukaryotes, plays a major role in signaling pathways that control many growth and developmental processes in plants as well as their responses to various biotic and abiotic stresses. Cellular changes in Ca2+ in response to diverse signals are recognized by protein sensors that either have their activity modulated or that interact with other proteins and modulate their activity. Cal-modulins (CaMs) and CaM-like proteins (CMLs) are Ca2+ sensors that have no enzymatic activity of their own but upon binding Ca2+ interact and modulate the activity of other proteins involved in a large number of plant processes. Protein-protein interactions play a key role in Ca2+/CaM-mediated in signaling pathways. In this review, using CaM as an example, we discuss various experimental approaches and computational tools to identify protein-protein interactions. During the last two decades hundreds of CaM-binding proteins in plants have been identified using a variety of approaches ranging from simple screening of expression libraries with labeled CaM to high-throughput screens using protein chips. However, the high-throughput methods have not been applied to the entire proteome of any plant system. Nevertheless, the data provided by these screens allows the development of computational tools to predict CaM-interacting proteins. Using all known binding sites of CaM, we developed a computational method that predicted over 700 high confidence CaM interactors in the Arabidopsis proteome. Most (>600) of these are not known to bind calmodulin, suggesting that there are likely many more CaM targets than previously known. Functional analyses of some of the experimentally identified Ca2+ sensor target proteins have uncovered their precise role in Ca2+-mediated processes. Further studies on identifying novel targets of CaM and CMLs and generating their interaction network - "calcium sensor interactome" - will help us in understanding how Ca2+ regulates a myriad of cellular and physiological processes. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1007 / 1019
页数:13
相关论文
共 50 条
  • [31] Identifying protein interactions - Experimental approaches
    Appella, E
    Anderson, CW
    FEBS JOURNAL, 2005, 272 (21) : 5389 - 5390
  • [32] Computational Approaches to the Study of Corruption
    Villamil, Isabela
    Kertész, János
    Wachs, Johannes
    arXiv, 2022,
  • [33] Editorial: Mechanobiology and the microenvironment: Computational and experimental approaches
    Mak, Michael
    Carlier, Aurelie
    Spill, Fabian
    Malandrino, Andrea
    Long, Mian
    Gomez-Benito Maria, Jose
    FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY, 2022, 10
  • [34] RNA dynamics from experimental and computational approaches
    Bussi, Giovanni
    Bonomi, Massimiliano
    Gkeka, Paraskevi
    Sattler, Michael
    Al-Hashimi, Hashim M.
    Auffinger, Pascal
    Duca, Maria
    Foricher, Yann
    Incarnato, Danny
    Jones, Alisha N.
    Kirmizialtin, Serdal
    Krepl, Miroslav
    Orozco, Modesto
    Palermo, Giulia
    Pasquali, Samuela
    Salmon, Loic
    Schwalbe, Harald
    Westhof, Eric
    Zacharias, Martin
    STRUCTURE, 2024, 32 (09) : 1281 - 1287
  • [35] Integration of experimental and computational approaches to sprouting angiogenesis
    Peirce, Shayn M.
    Mac Gabhann, Feilim
    Bautch, Victoria L.
    CURRENT OPINION IN HEMATOLOGY, 2012, 19 (03) : 184 - 191
  • [36] Regulatory genomics: Combined experimental and computational approaches
    E. V. Ignatieva
    O. A. Podkolodnaya
    Yu. L. Orlov
    G. V. Vasiliev
    N. A. Kolchanov
    Russian Journal of Genetics, 2015, 51 : 334 - 352
  • [37] Protein dynamics: Experimental and computational approaches Preface
    Bettati, Stefano
    Luque, F. Javier
    Viappiani, Cristiano
    BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS, 2011, 1814 (08): : 913 - 915
  • [38] Inductive Reasoning: Experimental, Developmental and Computational Approaches
    Evans, Jonathan St B. T.
    AMERICAN JOURNAL OF PSYCHOLOGY, 2010, 123 (01): : 118 - 121
  • [39] Experimental and Computational Analyses of Sustainable Approaches in Railways
    Farooq, Mohammad Adnan
    Meena, Naveen Kumar
    Punetha, Piyush
    Nimbalkar, Sanjay
    Lam, Nelson
    INFRASTRUCTURES, 2024, 9 (03)
  • [40] Regulatory genomics: Combined experimental and computational approaches
    Ignatieva, E. V.
    Podkolodnaya, O. A.
    Orlov, Yu L.
    Vasiliev, G. V.
    Kolchanov, N. A.
    RUSSIAN JOURNAL OF GENETICS, 2015, 51 (04) : 334 - 352