ESM-GP Protein-Protein Interaction Predictor

Model Description

ESM-GP is a sequence-based protein–protein interaction (PPI) predictor that uses a MLP backbone with a last-layer Gaussian process (LLGP). It produces a probability score for whether two proteins interact. This is an ablation of TUnA.

Intended Use

  • Research use for PPI prediction and representation learning.
  • These weights can be loaded in from the TUnA-R repository on Github.

Training Data

Trained on the Bernett dataset (https://academic.oup.com/bib/article/25/2/bbae076/7621029) composed of Human PPI interactions.

Model Architecture

Backbone: tuna.models._mlp.MLP

  • protein_dim: 640
  • hid_dim: 64
  • dropout: 0.1
  • llgp: True
  • use_spectral_norm: True
  • out_targets: 1
  • gp_config:
    • rff_features: 4096
    • gp_cov_momentum: -1
    • gp_ridge_penalty: 1
    • likelihood: "binary_logistic"

Evaluation Results (Test Set)

  • AUROC: 0.70
  • MCC: 0.27
  • Accuracy: 0.63
  • AUPRC: 0.69
  • Precision: 0.65

Citation

If you use this model, please cite:

License

MIT

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