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.