TM-Vec: template modeling vectors for fast homology detection and alignment: https://www.biorxiv.org/content/10.1101/2022.07.25.501437v1
First create a conda environment with python=3.9 installed. If you are using cpu, use
conda create -n tmvec faiss-cpu python=3.9 -c pytorch
If you are using gpu use
conda create -n tmvec faiss-gpu python=3.9 -c pytorch
Once your conda enviroment is installed and activated (i.e. conda activate tmvec), then install tm-vec via
pip install tm-vec. If you are using a GPU, you may need to reinstall the gpu version of pytorch.
See the pytorch webpage for more details.
Download the TM-vec model trained on SwissModel pairs:
wget https://users.flatironinstitute.org/thamamsy/public_www/tm_vec_swiss_model.ckpt
Download the TM-vec config file for the model trained on SwissModel pairs:
wget https://users.flatironinstitute.org/thamamsy/public_www/tm_vec_swiss_model_params.json
Download the TM-vec model trained on CATH pairs:
wget https://users.flatironinstitute.org/thamamsy/public_www/tm_vec_cath_model.ckpt
Download the TM-vec config file for model trained on CATH pairs:
wget https://users.flatironinstitute.org/thamamsy/public_www/tm_vec_cath_model_params.json