Introduction

Source code for Seq2Symm: Rapid and accurate prediction of protein homo-oligomer symmetry

Rapid prediction of homo-oligomer symmetries using a single sequence as input

Getting Started

Dependencies are in the yaml file esm2_finetune.yaml

conda env create --name esm2 --file=esm2_finetune.yaml

Downloads

1. the predictions from the model on various datasets, predictions on proteomes http://files.ipd.uw.edu/pub/seq2symm/predictions.zip

2. the trained model http://files.ipd.uw.edu/pub/seq2symm/ESM2_model.ckpt

Training the model

python src/finetune.py --meta_data_file ../datasets/homomer_pdbids_hash_clusterid_labels_sampled.csv --data_dir ../datasets/ --model_dir models/ --output_model seq2symm --output_dir outputs/seq2symm --bs 16 --data_splits_file ../datasets/train_val_test_splits.pkl --limit 65536 --granularity 3 --n_classes 20 --n_epoch 100 --weighted_sampler 1

Predicting using the model

A jupyter notebook is available at src/load_chkpt_and_predict.ipynb that shows examples of how this is done for two different file formats