Improved prediction of post-translational modification crosstalk within proteins using DeepPCT.

ABSTRACT:

Motivation

Post-translational modification (PTM) crosstalk events play critical roles in biological processes. Several machine learning methods have been developed to identify PTM crosstalk within proteins, but the accuracy is still far from satisfactory. Recent breakthroughs in deep learning and protein structure prediction could provide a potential solution to this issue.

Results

We proposed DeepPCT, a deep learning algorithm to identify PTM crosstalk using AlphaFold2-based structures. In this algorithm, one deep learning classifier was constructed for sequence-based prediction by combining the residue and residue pair embeddings with cross-attention techniques, while the other classifier was established for structure-based prediction by integrating the structural embeddin

SUBMITTER: Huang YX 

PROVIDER: S-EPMC11645436 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature