GPS-pPLM: A Language Model for Prediction of Prokaryotic Phosphorylation Sites.

ABSTRACT: In the prokaryotic kingdom, protein phosphorylation serves as one of the most important posttranslational modifications (PTMs) and is involved in orchestrating a broad spectrum of biological processes. Here, we report an updated online server named the group-based prediction system for prokaryotic phosphorylation language model (GPS-pPLM), used for predicting phosphorylation sites (p-sites) in prokaryotes. For model training, two deep learning methods, a transformer and a deep neural network, were employed, and a total of 10 sequence features and contextual features were integrated. Using 44,839 nonredundant p-sites in 16,041 proteins from 95 prokaryotes, two general models for the prediction of O-phosphorylation and N-phosphorylation were first pretrained and then fine-tuned

SUBMITTER: Zhang C 

PROVIDER: S-EPMC11593113 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature