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The Molecular Basis of JAZ-MYC Coupling, a Protein-Protein Interface Essential for Plant Response to Stressors

  • Samara Oña Chuquimarca
  • , Sebastián Ayala-Ruano
  • , Jonas Goossens
  • , Laurens Pauwels
  • , Alain Goossens
  • , Antonio Leon-Reyes*
  • , Miguel Ángel Méndez*
  • *Corresponding author for this work
  • Universidad San Francisco de Quito
  • Ghent University
  • VIB Center for Plant Systems Biology
  • University of North Carolina

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

The jasmonic acid (JA) signaling pathway is one of the primary mechanisms that allow plants to respond to a variety of biotic and abiotic stressors. Within this pathway, the JAZ repressor proteins and the basic helix-loop-helix (bHLH) transcription factor MYC3 play a critical role. JA is a volatile organic compound with an essential role in plant immunity. The increase in the concentration of JA leads to the decoupling of the JAZ repressor proteins and the bHLH transcription factor MYC3 causing the induction of genes of interest. The primary goal of this study was to identify the molecular basis of JAZ-MYC coupling. For this purpose, we modeled and validated 12 JAZ-MYC3 3D in silico structures and developed a molecular dynamics/machine learning pipeline to obtain two outcomes. First, we calculated the average free binding energy of JAZ-MYC3 complexes, which was predicted to be -10.94 +/-2.67 kJ/mol. Second, we predicted which ones should be the interface residues that make the predominant contribution to the free energy of binding (molecular hotspots). The predicted protein hotspots matched a conserved linear motif SL••FL•••R, which may have a crucial role during MYC3 recognition of JAZ proteins. As a proof of concept, we tested, both in silico and in vitro, the importance of this motif on PEAPOD (PPD) proteins, which also belong to the TIFY protein family, like the JAZ proteins, but cannot bind to MYC3. By mutating these proteins to match the SL••FL•••R motif, we could force PPDs to bind the MYC3 transcription factor. Taken together, modeling protein-protein interactions and using machine learning will help to find essential motifs and molecular mechanisms in the JA pathway.

Original languageEnglish
Article number1139
JournalFrontiers in Plant Science
Volume11
DOIs
StatePublished - 20 Aug 2020

Keywords

  • JAZ
  • MYC
  • computer
  • hotspots
  • machine learning
  • modeling
  • plant defense

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