PlantPhos

PlantPhos predicts kinase-specific phosphorylation sites in plant proteins to identify kinase–substrate relationships and support analysis of signal transduction networks.


Key Features:

  • Kinase-Specific Phosphorylation Data Integration: Incorporates kinase-specific phosphorylation data to consider substrate specificities unique to plant proteins.
  • Maximal Dependence Decomposition (MDD): Uses MDD to cluster 3006 experimentally verified phosphorylation events into subgroups with significantly conserved motifs, enabling identification of distinct kinase-associated substrate motifs.
  • Profile Hidden Markov Model (HMM): Develops profile HMMs for each MDD-clustered subgroup to create predictive models trained and validated using cross-validation techniques.
  • High Predictive Accuracy: Reports cross-validation accuracy of 82.4% for serine, 78.6% for threonine, and 89.0% for tyrosine predictions, and independent validation on UniProtKB/Swiss-Prot of 81.4% (phosphoserine), 77.1% (phosphothreonine), and 83.7% (phosphotyrosine).
  • Comparison to Existing Models: Demonstrates that MDD-clustered models outperform models that do not use MDD in capturing kinase-specific phosphorylation patterns.

Scientific Applications:

  • Intracellular Signal Transduction Research: Predicts phosphorylation sites to elucidate regulatory roles of protein kinases in plant signal transduction pathways.
  • Functional Genomics Studies: Identifies and characterizes kinase–substrate relationships in plant proteins to support functional genomics investigations.
  • Comparative Phosphorylation Analysis: Enables comparison of phosphorylation motifs across species to analyze evolutionary conservation and divergence in kinase signaling networks.

Methodology:

Integrates experimentally verified phosphorylation data from the TAIR9 database, applies Maximal Dependence Decomposition (MDD) to cluster phosphorylation events into motif-conserved subgroups, builds profile HMMs for each subgroup, and trains and validates predictive models using cross-validation and independent validation on UniProtKB/Swiss-Prot.

Topics

Details

Tool Type:
web application
Operating Systems:
Linux, Windows, Mac
Added:
8/3/2017
Last Updated:
11/25/2024

Operations

Publications

Lee T, Bretaña NA, Lu C. PlantPhos: using maximal dependence decomposition to identify plant phosphorylation sites with substrate site specificity. BMC Bioinformatics. 2011;12(1). doi:10.1186/1471-2105-12-261. PMID:21703007. PMCID:PMC3228547.

Documentation

Links