diffdock Model by MIT

mit/diffdockRUN ANYWHERE

Predicts the 3D structure of how a molecule interacts with a protein.

Docking

Drug Discovery

API Reference

By running the below commands, you accept the NVIDIA AI Enterprise Terms of Use and the NVIDIA Community Models License.

Pull and run mit/diffdock using Docker (this will download the full model and run it in your local environment)


$ docker login nvcr.io
Username: $oauthtoken
Password: <PASTE_API_KEY_HERE>

Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.


export NGC_API_KEY=<PASTE_API_KEY_HERE>

docker run -it --rm \
    --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=0 \
    --shm-size=2G \
    --ulimit memlock=-1 \
    --ulimit stack=67108864 \
    -e NGC_API_KEY=$NGC_API_KEY \
    -p 8000:8000 \
    nvcr.io/nim/mit/diffdock:2.0.0

You can now make a local API call using this curl command:


protein_bytes=`curl -s https://files.rcsb.org/download/8G43.pdb | grep -E '^ATOM' | sed -z 's/\n/\\\n/g'`; \
 ligand_bytes=`curl -s https://files.rcsb.org/ligands/download/ZU6_ideal.sdf | sed -z 's/\n/\\\n/g'`; \
 echo "{
     \"ligand\": \"${ligand_bytes}\",
     \"ligand_file_type\": \"sdf\",
     \"protein\": \"${protein_bytes}\",
     \"num_poses\": 1,
     \"time_divisions\": 20,
     \"steps\": 18,
     \"save_trajectory\": false,
     \"is_staged\": false
 }" > diffdock.json

curl --header "Content-Type: application/json" \
    --request POST \
    --data @diffdock.json \
    --output output.json \
    http://localhost:8000/molecular-docking/diffdock/generate

For more details on getting started with this NIM, visit the NVIDIA NIM Docs.