X-PAIR model checkpoints
This repository contains the trained model checkpoints used in X-PAIR, an ultrafast multitask framework for protein–protein interaction (PPI) and partner-specific interface prediction from protein sequences.
Model checkpoints
| Checkpoint | Task | Training dataset |
|---|---|---|
interaction_bernett.ckpt |
PPI prediction | Gold Standard (Bernett et al. ) |
interaction_dscript.ckpt |
PPI prediction | Cross-species benchmark (Sledzieski et al.) |
interface_pioneer.ckpt |
Interface prediction | PIONEER (Xiong et al.) |
interaction_xfair.ckpt |
PPI prediction | X-fair |
interface_xfair.ckpt |
Interface prediction | X-fair |
multitask_xfair.ckpt |
PPI + interface prediction | X-fair |
multitask_xhuman.ckpt |
PPI + interface prediction | X-human |
multitask_xmultispecies.ckpt |
PPI + interface prediction | X-multispecies |
Model
X-PAIR requires Python ≥3.10 and can be installed from PyPI:
pip install xpair
The complete X-PAIR source code is publicly available on GitLab.
Installation and usage instructions are provided in the repository README.
Detailed documentation describing the software functionality, input data formats, model architecture, and available workflows is available in the X-PAIR documentation.
A minimal demo is provided for training, evaluation, and prediction.
Data
The exact processed datasets used to train and evaluate the models are publicly available on Hugging Face.
Datasets generated as part of the X-PAIR study are additionally archived on Zenodo.
Citation
If you use X-PAIR, please cite:
Rescalli, S. & Carbone, A.
X-PAIR: an ultrafast multitask framework for proteome-scale reconstruction of PPI networks and partner-specific interfaces from sequence.
bioRxiv (2026).
https://doi.org/10.64898/2026.07.20.739596