GPS 5.0

GPS 5.0 predicts kinase-specific phosphorylation sites in proteins to facilitate analysis of kinase–substrate relationships and phosphorylation-mediated regulation in eukaryotes.

Key Features:

• Group-based prediction approach: Uses a group-based prediction system to model kinase-specific phosphorylation patterns.
• Position Weight Determination (PWD): Applies PWD to determine position-specific weights for scoring phosphorylation site motifs.
• Scoring Matrix Optimization (SMO): Employs SMO to optimize scoring matrices for improved prediction performance.
• Position-specific scoring matrices: Uses position-specific scoring matrices derived and optimized by PWD and SMO for site scoring.
• Kinase class coverage: Supports predictions for serine/threonine kinases, tyrosine kinases, and dual-specificity kinases.
• Classical module predictors: Contains 617 individual predictors targeting phosphorylation sites for 479 human PKs.
• Species-specific module coverage: Extends predictions across 44,795 PKs in 161 eukaryotic organisms for species-specific analysis.

Scientific Applications:

• Kinase–substrate mapping: Predicts kinase-specific p-sites to infer kinase–substrate relationships.
• Signaling pathway analysis: Identifies phosphorylation sites relevant to cellular signaling and regulation.
• Experimental design and validation: Guides selection of candidate p-sites for biochemical or mass-spectrometry validation experiments.
• Comparative and evolutionary studies: Enables cross-species analysis of phosphorylation by covering 161 eukaryotic organisms.

Methodology:

Implements a group-based prediction approach using position-specific scoring matrices optimized via Position Weight Determination (PWD) and Scoring Matrix Optimization (SMO).