area-science-park/ESM3-PPISites

Protein-Protein Interaction Site Prediction

This model is a finetuned version of ESM3-open for protein-protein interaction site prediction. It predicts whether a certain amino acid in a protein sequence is part of an interaction site (1) or not (0).

For more details on the training and testing on this model, refer to the article [...].

The github repository to use with this model is available here: https://github.com/RitAreaSciencePark/ESM3-PPISites

The data for the training and evaluation of this model is available in csv format in this zenodo repository: https://doi.org/10.5281/zenodo.18802482

How to Get Started with the Model

import torch
from transformers import AutoModel, AutoTokenizer, AutoConfig
model_name = "area-science-park/ESM3-PPISites"
model = AutoModel.from_pretrained(model_name, trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
# move model to device
device = "cuda" if torch.cuda.is_available() else "cpu"
model = model.to(device)
# run over a sample sequence
sequence = "MKTVRQERLKSIVRILEAAKEPVSGAQLAEELSVSRQVIVQDIAYLRSLGYNIVATPRGYVLAGG"
inputs = tokenizer.encode(sequence, return_tensors="pt").to(device)
logits = model(inputs)["logits"]
probabilities = torch.sigmoid(logits)
# get predictions
probabilities

References