NetPhorest

NetPhorest maps kinase consensus sequence motifs and phosphorylation-dependent binding domains to predict kinase–substrate relationships and binding-domain engagements for quantitative analysis of phosphorylation-dependent signaling networks.

Key Features:

• Extensive Coverage: Provides consensus sequence motifs for 179 kinases and 104 phosphorylation-dependent binding domains, including Src homology 2 (SH2), phosphotyrosine binding (PTB), BRCA1 C-terminal (BRCT), WW, and 14-3-3.
• Insights into Kinase Specificity: Highlights that tyrosine kinases mutated in cancer exhibit lower specificity compared to their non-oncogenic counterparts.
• Automated Maintenance: Maintained via an automated pipeline that leverages phylogenetic trees to organize available in vivo and in vitro data, ensuring sequence models are probabilistically robust.
• Probabilistic Sequence Models: Derives probabilistic models of linear motifs to provide a quantitative framework for predicting kinase-substrate interactions and binding domain engagements.

Scientific Applications:

• Signal Transduction Research: Maps kinases to substrates and phosphorylation-dependent binding partners to aid elucidation of complex signaling networks.
• Cancer Biology: Provides specificity data on kinases mutated in cancer that can inform studies of oncogenic signaling and therapeutic targeting.
• Systems Biology: Enables integration of phosphorylation and binding-domain interaction predictions into broader models of cellular behavior and response mechanisms.

Methodology:

Uses phylogenetic trees and an automated pipeline to organize in vivo and in vitro data and to derive probabilistic sequence models of linear phosphorylation motifs.