diff --git a/tutorials-and-examples/nvidia-nim/blueprints/README.md b/tutorials-and-examples/nvidia-nim/blueprints/README.md
new file mode 100644
index 000000000..1c7f51c47
--- /dev/null
+++ b/tutorials-and-examples/nvidia-nim/blueprints/README.md
@@ -0,0 +1,8 @@
+### NVIDIA NIM Blueprints on GKE
+
+Here you will find the NVIDIA NIM Blueprints that can be provisioned to run on GKE. These are good for proof of concepts only.
+
+- [ ] [Generative Virtual Screening for Drug Discovery](./drugdiscovery/README.md) uses 3 NIMs
+  - AlphaFold2
+  - MolMIM
+  - DiffDock
diff --git a/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/README.md b/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/README.md
new file mode 100644
index 000000000..64442ed11
--- /dev/null
+++ b/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/README.md
@@ -0,0 +1,177 @@
+# Generative Virtual Screening for Drug Discovery on GKE
+
+This guide outlines the steps to deploy NVIDIA's NIM blueprint for [Generative Virtual screening for Drug Discovery](https://build.nvidia.com/nvidia/generative-virtual-screening-for-drug-discovery) on a Google Kubernetes Engine (GKE) cluster. Three NIMs - AlphaFold2, MolMIM & DiffDock are used to demonstrate Protein folding, molecular generation and protein docking.
+
+## Prerequisites
+
+* **GCloud SDK:** Ensure you have the Google Cloud SDK installed and configured.
+* **Project:**  A Google Cloud project with billing enabled.
+* **NGC API Key:** An API key from NVIDIA NGC.
+* **kubectl:**  kubectl command-line tool installed and configured.
+
+Clone the repo before proceeding further:
+`git clone https://github.com/GoogleCloudPlatform/ai-on-gke`
+`cd ai-on-gke/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery`
+
+## Deployment Steps
+
+1. **Set Project and Variables:**
+
+    ```bash
+
+    gcloud config set project "<GCP Project ID>"
+    export PROJECT_ID=$(gcloud config get project)
+    export CLUSTER_NAME="gke-nimbp-genscr"
+    export NODE_POOL_NAME="gke-nimbp-genscr-np"
+    export ZONE="<GCP zone>" #us-east5-b
+    export MACHINE_TYPE= "<GCP machine type>" #"a2-ultragpu-1g"
+    export ACCELERATOR_TYPE="<GPU Type>" #"nvidia-a100-80gb"
+    export ACCELERATOR_COUNT="1"
+    export NODE_POOL_NODES=3
+    export NGC_API_KEY="<NGC API Key>"
+
+    ```
+
+2. **Create GKE Cluster:** This creates the initial cluster with a default node pool for management tasks. GPU nodes will be added in the next step.
+
+    ```bash
+
+    gcloud container clusters create "${CLUSTER_NAME}" \
+      --project="${PROJECT_ID}" \
+      --num-nodes=1 --location="${ZONE}" \
+      --machine-type=e2-standard-16 \
+      --addons=GcpFilestoreCsiDriver
+  
+    ```
+
+3. **Create GPU Node Pool:** This creates a node pool with GPU machines optimized for BioNeMo workloads.
+
+    ```bash
+
+    gcloud container node-pools create "${NODE_POOL_NAME}" \
+        --cluster="${CLUSTER_NAME}" \
+        --location="${ZONE}" \
+        --node-locations="${ZONE}" \
+        --num-nodes="${NODE_POOL_NODES}" \
+        --machine-type="${MACHINE_TYPE}" \
+        --accelerator="type=${ACCELERATOR_TYPE},count=${ACCELERATOR_COUNT},gpu-driver-version=LATEST" \
+        --placement-type="COMPACT" \
+        --disk-type="pd-ssd" \
+        --disk-size="500GB"
+    
+    ```
+
+4. **Get Cluster Credentials:**
+
+    ```bash
+
+    gcloud container clusters get-credentials "${CLUSTER_NAME}" --location="${ZONE}"
+
+    ```
+
+5. **Set kubectl Alias (Optional):**
+
+    ```bash
+    
+    alias k=kubectl
+
+    ```
+
+6. **Create NGC Secret:** Creates the secret for pulling images from NVIDIA NGC.  **Important:** Replace the placeholder API key with your actual NGC API Key.
+
+    ```bash
+
+    k create secret docker-registry secret-nvcr \
+      --docker-username=\$oauthtoken \
+      --docker-password="${NGC_API_KEY}" \
+      --docker-server="nvcr.io"
+    
+    ```
+
+7. **Deploy BioNeMo Services:** Deploy AlphaFold2, MolMIM, and DiffDock.
+
+    ```bash
+
+    k create -f nim-storage-filestore.yaml
+    k create -f nim-bionemo-generative-virtual-screening.yaml 
+
+    ```
+
+8. **Port Forwarding (for local testing):**  These commands forward the service ports to your local machine for testing. Replace the pod names with the actual names of your deployed pods.
+
+    ```bash
+
+    POD_BIONEMO_ALPHAFOLD=$(k get pods -o go-template --template '{{range .items}}{{.metadata.name}}{{"\n"}}{{end}}' | grep '^alphafold2')
+    k port-forward pod/$POD_BIONEMO_ALPHAFOLD :8000
+
+    POD_BIONEMO_MOLMIM=$(k get pods -o go-template --template '{{range .items}}{{.metadata.name}}{{"\n"}}{{end}}' | grep '^molmim')
+    k port-forward pod/$POD_BIONEMO_MOLMIM :8000
+    
+    POD_BIONEMO_DIFFDOCK=$(k get pods -o go-template --template '{{range .items}}{{.metadata.name}}{{"\n"}}{{end}}' | grep '^diffdock')
+    k port-forward pod/$POD_BIONEMO_DIFFDOCK :8000
+  
+    ```
+
+9. **Test Deployments:**  Use `curl` or other tools to test the deployed services by sending requests to the forwarded ports.  Examples are provided in the `dev.sh` file.
+
+    ```bash
+  
+    # AlphaFold2
+    curl \
+    --max-time 900 \
+    -X POST \
+    -i \
+    "http://localhost:62921/protein-structure/alphafold2/predict-structure-from-sequence" \
+    -H 'accept: application/json' \
+    -H 'Content-Type: application/json' \
+    -d '{
+      "sequence": "MVPSAGQLALFALGIVLAACQALENSTSPLSADPPVAAAVVSHFNDCPDSHTQFCFHGTCRFLVQEDKPACVCHSGYVGARCEHADLLAVVAASQKKQAITALVVVSIVALAVLIITCVLIHCCQVRKHCEWCRALICRHEKPSALLKGRTACCHSETVV",
+      "databases": [
+        "small_bfd"
+      ]
+    }'
+  
+    ```
+  
+    ```bash
+  
+    # MolMIM
+    curl -X POST \
+    -H 'Content-Type: application/json' \
+    -d '{
+      "smi": "CC1(C2C1C(N(C2)C(=O)C(C(C)(C)C)NC(=O)C(F)(F)F)C(=O)NC(CC3CCNC3=O)C#N)C",
+      "num_molecules": 5,
+      "algorithm": "CMA-ES",
+      "property_name": "QED",
+      "min_similarity": 0.7,
+      "iterations": 10
+    }' \
+    "http://localhost:49530/generate"
+  
+    ```
+
+10. **Test end to end:**
+    Update the AF2_HOST, MOLMIM_HOST and DIFFDOCK_HOST variables with port numbers in `test-generative-virtual-screening.py` file.
+
+    ```bash
+
+    python3 -m venv venv
+    source venv/bin/activate
+    pip3 install requests
+    python3 test-generative-virtual-screening.py
+    deactivate
+
+    ```
+
+## Cleanup
+
+   To delete the cluster and all associated resources:
+
+   ```bash
+
+   k delete secret secret-nvcr
+   k delete -f nim-bionemo-generative-virtual-screening.yaml
+   k delete -f nim-storage-filestore.yaml
+   gcloud container clusters delete "${CLUSTER_NAME}" --location="${ZONE}"
+
+   ```
diff --git a/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/nim-bionemo-generative-virtual-screening.yaml b/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/nim-bionemo-generative-virtual-screening.yaml
new file mode 100644
index 000000000..77264257e
--- /dev/null
+++ b/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/nim-bionemo-generative-virtual-screening.yaml
@@ -0,0 +1,189 @@
+---
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: alphafold2
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: alphafold2
+  template:
+    metadata:
+      labels:
+        app: alphafold2
+    spec:
+      containers:
+      - name: alphafold2
+        image: nvcr.io/nim/deepmind/alphafold2:2.1.0
+        securityContext:
+          runAsUser: 0
+        ports:
+        - containerPort: 8000
+        volumeMounts:
+        - name: alphafold2-cache
+          mountPath: /data
+        env:
+        - name: NGC_API_KEY
+          valueFrom:
+            secretKeyRef:
+              name: ngc-api-key  # Replace with your actual secret name
+              key: NGC_API_KEY
+        - name: NIM_CACHE_PATH
+          value: /data
+        - name: NIM_MODEL_ORG
+          value: nim
+        - name: NIM_MODEL_TEAM
+          value: deepmind
+        resources:
+          requests:
+            nvidia.com/gpu: 1
+          limits:
+            nvidia.com/gpu: 1
+      volumes:
+      - name: alphafold2-cache
+        persistentVolumeClaim:
+          claimName: nim-storage-filestore
+      imagePullSecrets:
+      - name: secret-nvcr
+
+---
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: molmim
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: molmim
+  template:
+    metadata:
+      labels:
+        app: molmim
+    spec:
+      containers:
+      - name: molmim
+        image: nvcr.io/nim/nvidia/molmim:1.0.0
+        securityContext:
+          runAsUser: 0
+        ports:
+        - containerPort: 8000
+        volumeMounts:
+        - name: molmim-cache
+          mountPath: /data
+        env:
+        - name: NGC_API_KEY
+          valueFrom:
+            secretKeyRef:
+              name: ngc-api-key  # Replace with your actual secret name
+              key: NGC_API_KEY
+        - name: NIM_CACHE_PATH
+          value: /data
+        resources:
+          requests:
+            nvidia.com/gpu: 1
+          limits:
+            nvidia.com/gpu: 1
+      volumes:
+      - name: molmim-cache
+        persistentVolumeClaim:
+          claimName: nim-storage-filestore
+      imagePullSecrets:
+      - name: secret-nvcr
+
+---
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: diffdock
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: diffdock
+  template:
+    metadata:
+      labels:
+        app: diffdock
+    spec:
+      containers:
+      - name: diffdock
+        image: nvcr.io/nim/mit/diffdock:2.0
+        securityContext:
+          runAsUser: 0
+        ports:
+        - containerPort: 8000
+        volumeMounts:
+        - name: diffdock-cache
+          mountPath: /data
+        env:
+        - name: NGC_API_KEY
+          valueFrom:
+            secretKeyRef:
+              name: ngc-api-key  # Replace with your actual secret name
+              key: NGC_API_KEY
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: "0"  # Set the default value here
+        - name: NIM_CACHE_PATH
+          value: /data
+        resources:
+          requests:
+            nvidia.com/gpu: 1
+          limits:
+            nvidia.com/gpu: 1
+      imagePullSecrets:
+      - name: secret-nvcr
+      volumes:
+      - name: diffdock-cache
+        persistentVolumeClaim:
+          claimName: nim-storage-filestore
+
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: alphafold2-service
+spec:
+  selector:
+    app: alphafold2
+  ports:
+  - protocol: TCP
+    port: 8081
+    targetPort: 8000
+
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: diffdock-service
+spec:
+  selector:
+    app: diffdock
+  ports:
+  - protocol: TCP
+    port: 8082
+    targetPort: 8000
+
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: molmim-service
+spec:
+  selector:
+    app: molmim
+  ports:
+  - protocol: TCP
+    port: 8083
+    targetPort: 8000
+
+---
+# Create a Secret to hold the NGC API key
+apiVersion: v1
+kind: Secret
+metadata:
+  name: ngc-api-key
+type: Opaque
+stringData:
+  NGC_API_KEY: <NGC API Key>
\ No newline at end of file
diff --git a/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/nim-storage-filestore.yaml b/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/nim-storage-filestore.yaml
new file mode 100644
index 000000000..6e0434b1d
--- /dev/null
+++ b/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/nim-storage-filestore.yaml
@@ -0,0 +1,24 @@
+apiVersion: storage.k8s.io/v1
+kind: StorageClass
+metadata:
+  name: nim-storage-filestore
+provisioner: filestore.csi.storage.gke.io
+volumeBindingMode: Immediate
+allowVolumeExpansion: true
+parameters:
+  tier: BASIC_SSD
+  network: default
+---
+kind: PersistentVolumeClaim
+apiVersion: v1
+metadata:
+  name: nim-storage-filestore
+  namespace: default
+spec:
+  accessModes:
+  - ReadWriteMany
+  storageClassName: nim-storage-filestore
+  resources:
+    requests:
+      storage: 2.5Ti
+
diff --git a/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/test-generative-virtual-screening.py b/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/test-generative-virtual-screening.py
new file mode 100644
index 000000000..ecd076d9a
--- /dev/null
+++ b/tutorials-and-examples/nvidia-nim/blueprints/drugdiscovery/test-generative-virtual-screening.py
@@ -0,0 +1,110 @@
+import requests
+
+AF2_HOST = "http://localhost:<replace with port number>"
+MOLMIM_HOST = "http://localhost:<replace with port number>"
+DIFFDOCK_HOST = "http://localhost:<replace with port number>"
+
+
+def check_readiness(service_name, url):
+    try:
+        response = requests.get(url)
+        response.raise_for_status()  # Raise an exception for bad status codes
+        print(f"{service_name} readiness check successful at {url}.")
+        return True
+    except requests.exceptions.RequestException as e:
+        print(f"{service_name} readiness check failed: {e}")
+        return False
+
+
+check_readiness("AlphaFold2", f"{AF2_HOST}/v1/health/ready")
+check_readiness("MolMIM", f"{MOLMIM_HOST}/v1/health/ready")
+check_readiness("DiffDock", f"{DIFFDOCK_HOST}/v1/health/ready")
+
+
+## AlphaFold2 NIM
+protein_sequence = "MVPSAGQLALFALGIVLAACQALENSTSPLSADPPVAAAVVSHFNDCPDSHTQFCFHGTCRFLVQEDKPACVCHSGYVGARCEHADLLAVVAASQKKQAITALVVVSIVALAVLIITCVLIHCCQVRKHCEWCRALICRHEKPSALLKGRTACCHSETVV"
+
+print("Protein folding with AlphaFold2...")  # Progress update
+try:
+    af2_response = requests.post(
+        f"{AF2_HOST}/protein-structure/alphafold2/predict-structure-from-sequence",
+        json={
+            "sequence": protein_sequence,
+            "databases": ["small_bfd"],
+        },
+    )
+    af2_response.raise_for_status()  # Check for HTTP errors
+    folded_protein = af2_response.json()[0]
+    print("Protein folding successfully.")  # Progress update
+
+except requests.exceptions.RequestException as e:
+    print(f"AlphaFold2 request failed: {e}")
+    exit(1)  # Exit if AlphaFold2 fails
+except IndexError:
+    print("Invalid response from AlphaFold2 (missing structure).")
+    exit(1)
+
+## MolMIM NIM
+molecule = "CC1(C2C1C(N(C2)C(=O)C(C(C)(C)C)NC(=O)C(F)(F)F)C(=O)NC(CC3CCNC3=O)C#N)C"
+
+print("Generating molecules with MolMIM...")  # Progress update
+try:
+    molmim_response = requests.post(
+        f"{MOLMIM_HOST}/generate",
+        json={
+            "smi": molecule,
+            "num_molecules": 5,
+            "algorithm": "CMA-ES",
+            "property_name": "QED",
+            "min_similarity": 0.7,  # Ignored if algorithm is not "CMA-ES".
+            "iterations": 10,
+        },
+    )
+    molmim_response.raise_for_status()  # Check for HTTP errors
+    molmim_response = molmim_response.json()
+
+    # Validate the response (check if 'generated' key exists and is a list)
+    if "generated" not in molmim_response or not isinstance(
+        molmim_response["generated"], list
+    ):
+        raise ValueError("Invalid response format from MolMIM")
+
+    generated_ligands = "\n".join([v["smiles"] for v in molmim_response["generated"]])
+    print(generated_ligands)
+    print("Molecular generation successfully.")  # Progress update
+
+except requests.exceptions.RequestException as e:
+    print(f"MolMIM request failed: {e}")
+    exit(1)  # Exit if MolMIM fails
+except ValueError as e:
+    print(f"Error processing MolMIM response: {e}")
+    exit(1)
+
+## DiffDock NIM
+diffdock_response = requests.post(
+    f"{DIFFDOCK_HOST}/molecular-docking/diffdock/generate",
+    json={
+        "protein": folded_protein,
+        "ligand": generated_ligands,
+        "ligand_file_type": "txt",
+        "num_poses": 10,
+        "time_divisions": 20,
+        "num_steps": 18,
+    },
+).json()
+
+print("Protein-ligand docking with DiffDock...")  # Progress update
+
+# Example assuming diffdock_response["ligand_positions"] is a list of lists.
+try:
+    for i in range(len(diffdock_response["ligand_positions"])):
+        print("*" * 80)
+        print(f"Docking result {i+1}:")  # More descriptive output
+        print(
+            diffdock_response["ligand_positions"][i][0]
+        )  # Print the first pose for now.  Handle multiple poses if needed.
+    print("Protein-ligand docking successful")  # Progress update
+
+except requests.exceptions.RequestException as e:
+    print(f"Error processing DiffDock results: Invalid response format: {e}")
+    exit(1)  # Exit if MolMIM fails