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2024;47 (1): e20230068.

Structure-based prediction of protein-protein interaction network in rice.

Fangnan Sun, Yaxin Deng, Xiaosong Ma, Yuan Liu, Lingxia Zhao, Shunwu Yu, Lida Zhang
Author Information
  1. Fangnan Sun: Shanghai Jiao Tong University, School of Agriculture and Biology, Department of Plant Science, Shanghai, China.
  2. Yaxin Deng: Shanghai Jiao Tong University, School of Agriculture and Biology, Department of Plant Science, Shanghai, China.
  3. Xiaosong Ma: Shanghai Academy of Agricultural Sciences, Shanghai Agrobiological Gene Center, Shanghai, China.
  4. Yuan Liu: Shanghai Jiao Tong University, School of Agriculture and Biology, Department of Plant Science, Shanghai, China.
  5. Lingxia Zhao: Shanghai Jiao Tong University, School of Agriculture and Biology, Department of Plant Science, Shanghai, China.
  6. Shunwu Yu: Shanghai Academy of Agricultural Sciences, Shanghai Agrobiological Gene Center, Shanghai, China. ORCID
  7. Lida Zhang: Shanghai Jiao Tong University, School of Agriculture and Biology, Department of Plant Science, Shanghai, China. ORCID
PMID: 38314883 DOI: 10.1590/1678-4685-GMB-2023-0068

Abstract

Comprehensive protein-protein interaction (PPI) maps are critical for understanding the functional organization of the proteome, but challenging to produce experimentally. Here, we developed a computational method for predicting PPIs based on protein docking. Evaluation of performance on benchmark sets demonstrated the ability of the docking-based method to accurately identify PPIs using predicted protein structures. By employing the docking-based method, we constructed a structurally resolved PPI network consisting of 24,653 interactions between 2,131 proteins, which greatly extends the current knowledge on the rice protein-protein interactome. Moreover, we mapped the trait-associated single nucleotide polymorphisms (SNPs) to the structural interactome, and computationally identified 14 SNPs that had significant consequences on PPI network. The protein structural interactome map provided a resource to facilitate functional investigation of PPI-perturbing alleles associated with agronomically important traits in rice.

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Journal Article

Word Cloud

Created with Highcharts 10.0.0protein-proteinPPImethodproteinnetworkriceinteractomeinteractionfunctionalPPIsdocking-basedSNPsstructuralComprehensivemapscriticalunderstandingorganizationproteomechallengingproduceexperimentallydevelopedcomputationalpredictingbaseddockingEvaluationperformancebenchmarksetsdemonstratedabilityaccuratelyidentifyusingpredictedstructuresemployingconstructedstructurallyresolvedconsisting24653interactions2131proteinsgreatlyextendscurrentknowledgeMoreovermappedtrait-associatedsinglenucleotidepolymorphismscomputationallyidentified14significantconsequencesmapprovidedresourcefacilitateinvestigationPPI-perturbingallelesassociatedagronomicallyimportanttraitsStructure-basedprediction

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