NetPhosBac

NetPhosBac predicts serine and threonine phosphorylation sites in bacterial proteins to support studies of bacterial signaling and regulation.

Key Features:

• Prediction targets: Serine and threonine phosphorylation sites in bacterial proteins.
• Training data: Large datasets derived from gel-free high accuracy mass spectrometry (MS) studies, including sites identified in Bacillus subtilis and Escherichia coli.
• Algorithm: Neural network algorithms tailored specifically for bacterial proteins.
• Taxa-specific modeling: Captures bacterial phosphorylation patterns that differ from eukaryotic-type protein kinase motifs.
• Benchmark performance: Demonstrated superior performance compared to predictors trained on eukaryotic data when applied to bacterial phosphorylation sites.
• Experimental validation: Predictions experimentally verified at protein- and site-specific levels in Escherichia coli.

Scientific Applications:

• Bacterial signaling and regulation studies: Identification of phosphorylated residues to study signaling pathways and regulatory mechanisms in bacteria.
• Proteome annotation: Annotation of phosphorylation sites in bacterial proteomes such as Bacillus subtilis and Escherichia coli.
• Comparative phosphorylation analysis: Comparison of bacterial phosphorylation patterns with eukaryotic phosphorylation to investigate motif differences.
• Experimental prioritization: Selection of candidate phosphorylation sites for targeted experimental validation in bacterial systems.

Methodology:

Training on large gel-free high accuracy mass spectrometry (MS) datasets and application of neural network algorithms tailored for bacterial proteins.