GPS-PBS: A Deep Learning Framework to Predict Phosphorylation Sites that Specifically Interact with Phosphoprotein-Binding Domains

Cells. 2020 May 20;9(5):1266. doi: 10.3390/cells9051266.


Protein phosphorylation is essential for regulating cellular activities by modifying substrates at specific residues, which frequently interact with proteins containing phosphoprotein-binding domains (PPBDs) to propagate the phosphorylation signaling into downstream pathways. Although massive phosphorylation sites (p-sites) have been reported, most of their interacting PPBDs are unknown. Here, we collected 4458 known PPBD-specific binding p-sites (PBSs), considerably improved our previously developed group-based prediction system (GPS) algorithm, and implemented a deep learning plus transfer learning strategy for model training. Then, we developed a new online service named GPS-PBS, which can hierarchically predict PBSs of 122 single PPBD clusters belonging to two groups and 16 families. By comparison, GPS-PBS achieved a highly competitive accuracy against other existing tools. Using GPS-PBS, we predicted 371,018 mammalian p-sites that potentially interact with at least one PPBD, and revealed that various PPBD-containing proteins (PPCPs) and protein kinases (PKs) can simultaneously regulate the same p-sites to orchestrate important pathways, such as the PI3K-Akt signaling pathway. Taken together, we anticipate GPS-PBS can be a great help for further dissecting phosphorylation signaling networks.

Keywords: PPBD-specific binding p-site; deep learning; phosphoprotein-binding domain; phosphorylation site; protein kinase; protein phosphorylation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Animals
  • Binding Sites
  • Databases, Protein
  • Deep Learning*
  • Humans
  • Phosphoproteins / chemistry*
  • Phosphoproteins / metabolism*
  • Phosphorylation
  • Protein Binding
  • Protein Domains
  • Proteome / metabolism
  • Signal Transduction
  • Statistics as Topic


  • Phosphoproteins
  • Proteome