Update

.ipynb_checkpoints/app-checkpoint.py

@@ -234,7 +234,7 @@ reps =    [
 
 # Gradio UI
 with gr.Blocks() as demo:
-    gr.Markdown("# Protein Binding Site Prediction (Random Scores)")
+    gr.Markdown("# Protein Binding Site Prediction")
     with gr.Row():
         pdb_input = gr.Textbox(value="2IWI", label="PDB ID", placeholder="Enter PDB ID here...")
         visualize_btn = gr.Button("Visualize Structure")
@@ -244,7 +244,7 @@ with gr.Blocks() as demo:
     with gr.Row():
         #pdb_input = gr.Textbox(value="2IWI", label="PDB ID", placeholder="Enter PDB ID here...")
         segment_input = gr.Textbox(value="A", label="Chain ID", placeholder="Enter Chain ID here...")
-        prediction_btn = gr.Button("Predict Random Binding Site Scores")
+        prediction_btn = gr.Button("Predict Binding Site")
 
     molecule_output = gr.HTML(label="Protein Structure")
     predictions_output = gr.Textbox(label="Binding Site Predictions")

.ipynb_checkpoints/test-checkpoint.ipynb

@@ -2,15 +2,15 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "id": "d2208d17-47b6-4ff1-b6b6-ba09a9d490c7",
+   "execution_count": 3,
+   "id": "1f8ea359-674c-4263-9c2a-7a8e7e464249",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "* Running on local URL:  http://127.0.0.1:7864\n",
+      "* Running on local URL:  http://127.0.0.1:7862\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
@@ -18,7 +18,7 @@
     {
      "data": {
       "text/html": [
-       "<div><iframe src=\"http://127.0.0.1:7864/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+       "<div><iframe src=\"http://127.0.0.1:7862/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -31,7 +31,7 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 5,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -145,33 +145,9 @@
    "source": []
   },
   {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "a1088e14-f09c-48ff-8632-cc4685306d7c",
+   "cell_type": "raw",
+   "id": "88affe12-7c48-4bd6-9e46-32cdffa729fe",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "* Running on local URL:  http://127.0.0.1:7863\n",
-      "\n",
-      "To create a public link, set `share=True` in `launch()`.\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div><iframe src=\"http://127.0.0.1:7863/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
    "source": [
     "import gradio as gr\n",
     "from gradio_molecule3d import Molecule3D\n",
@@ -248,17 +224,409 @@
    "outputs": [],
    "source": []
   },
+  {
+   "cell_type": "raw",
+   "id": "2b970adb-3152-427f-bb58-b92974ff406e",
+   "metadata": {},
+   "source": [
+    "import gradio as gr\n",
+    "import os\n",
+    "import requests\n",
+    "from Bio.PDB import PDBParser, PDBIO\n",
+    "import biotite.structure.io as bsio\n",
+    "\n",
+    "def read_mol(pdb_path):\n",
+    "    \"\"\"Read PDB file and return its content as a string\"\"\"\n",
+    "    with open(pdb_path, 'r') as f:\n",
+    "        return f.read()\n",
+    "\n",
+    "# Function to fetch or upload the PDB file\n",
+    "def get_pdb(pdb_code=\"\", filepath=\"\"):\n",
+    "    if pdb_code and len(pdb_code) == 4:\n",
+    "        pdb_file = f\"{pdb_code}.pdb\"\n",
+    "        if not os.path.exists(pdb_file):\n",
+    "            os.system(f\"wget -qnc https://files.rcsb.org/view/{pdb_code}.pdb\")\n",
+    "        return pdb_file\n",
+    "    elif filepath is not None:\n",
+    "        return filepath\n",
+    "    else:\n",
+    "        return None\n",
+    "\n",
+    "def molecule(input_pdb):\n",
+    "    mol = read_mol(input_pdb)  # Read PDB file content\n",
+    "    \n",
+    "    html_content = f\"\"\"\n",
+    "    <!DOCTYPE html>\n",
+    "    <html>\n",
+    "    <head>    \n",
+    "        <meta http-equiv=\"content-type\" content=\"text/html; charset=UTF-8\" />\n",
+    "        <style>\n",
+    "        .mol-container {{\n",
+    "            width: 100%;\n",
+    "            height: 700px;\n",
+    "            position: relative;\n",
+    "        }}\n",
+    "        </style>\n",
+    "        <script src=\"https://cdnjs.cloudflare.com/ajax/libs/jquery/3.6.3/jquery.min.js\"></script>\n",
+    "        <script src=\"https://3Dmol.csb.pitt.edu/build/3Dmol-min.js\"></script>\n",
+    "    </head>\n",
+    "    <body>\n",
+    "        <div id=\"container\" class=\"mol-container\"></div>\n",
+    "        <script>\n",
+    "            let pdb = `{mol}`; // Use template literal to properly escape PDB content\n",
+    "            $(document).ready(function () {{\n",
+    "                let element = $(\"#container\");\n",
+    "                let config = {{ backgroundColor: \"white\" }};\n",
+    "                let viewer = $3Dmol.createViewer(element, config);\n",
+    "                viewer.addModel(pdb, \"pdb\");\n",
+    "                viewer.getModel(0).setStyle({{}}, {{ cartoon: {{ colorscheme:\"whiteCarbon\" }} }});\n",
+    "                viewer.zoomTo();\n",
+    "                viewer.render();\n",
+    "                viewer.zoom(0.8, 2000);\n",
+    "            }});\n",
+    "        </script>\n",
+    "    </body>\n",
+    "    </html>\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    # Return the HTML content within an iframe safely encoded for special characters\n",
+    "    return f'<iframe width=\"100%\" height=\"700\" srcdoc=\"{html_content.replace(chr(34), \"&quot;\").replace(chr(39), \"&#39;\")}\"></iframe>'\n",
+    "\n",
+    "# Gradio function to update the visualization\n",
+    "def update(inp, file):\n",
+    "    pdb_path = get_pdb(inp, file)\n",
+    "    if pdb_path:\n",
+    "        return molecule(pdb_path)\n",
+    "    else:\n",
+    "        return \"Invalid input. Please provide a valid PDB code or upload a PDB file.\"\n",
+    "\n",
+    "# Gradio UI\n",
+    "demo = gr.Blocks()\n",
+    "with demo:\n",
+    "    gr.Markdown(\"# PDB Viewer using 3Dmol.js\")\n",
+    "    with gr.Row():\n",
+    "        with gr.Column():\n",
+    "            inp = gr.Textbox(\n",
+    "                placeholder=\"PDB Code or upload file below\", label=\"Input structure\"\n",
+    "            )\n",
+    "            file = gr.File(file_count=\"single\")\n",
+    "            btn = gr.Button(\"View structure\")\n",
+    "        mol = gr.HTML()\n",
+    "    btn.click(fn=update, inputs=[inp, file], outputs=mol)\n",
+    "\n",
+    "# Launch the Gradio interface \n",
+    "demo.launch(debug=True)"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "id": "cdf7fd26-0464-40d9-9107-71c29dbcaef8",
+   "execution_count": null,
+   "id": "ee215c16-a1fb-450f-bb93-37aaee6fb3f1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "raw",
+   "id": "050aa2e8-2dbe-4a28-8692-58ca7c50fccd",
+   "metadata": {},
+   "source": [
+    "import gradio as gr\n",
+    "import os\n",
+    "import requests\n",
+    "import numpy as np\n",
+    "from Bio.PDB import PDBParser\n",
+    "\n",
+    "def read_mol(pdb_path):\n",
+    "    \"\"\"Read PDB file and return its content as a string\"\"\"\n",
+    "    with open(pdb_path, 'r') as f:\n",
+    "        return f.read()\n",
+    "\n",
+    "# Function to fetch a PDB file from RCSB PDB\n",
+    "def fetch_pdb(pdb_id):\n",
+    "    pdb_url = f'https://files.rcsb.org/download/{pdb_id}.pdb'\n",
+    "    pdb_path = f'{pdb_id}.pdb'\n",
+    "    response = requests.get(pdb_url)\n",
+    "    if response.status_code == 200:\n",
+    "        with open(pdb_path, 'wb') as f:\n",
+    "            f.write(response.content)\n",
+    "        return molecule(pdb_path)\n",
+    "    else:\n",
+    "        return None\n",
+    "\n",
+    "# Function to process the PDB file and return random predictions\n",
+    "def process_pdb(pdb_id, segment):\n",
+    "    pdb_path = fetch_pdb(pdb_id)\n",
+    "    if not pdb_path:\n",
+    "        return \"Failed to fetch PDB file\", None, None\n",
+    "    \n",
+    "    parser = PDBParser(QUIET=True)\n",
+    "    structure = parser.get_structure('protein', pdb_path)\n",
+    "    \n",
+    "    try:\n",
+    "        chain = structure[0][segment]\n",
+    "    except KeyError:\n",
+    "        return \"Invalid Chain ID\", None, None\n",
+    "    \n",
+    "    sequence = [residue.get_resname() for residue in chain if residue.id[0] == ' ']\n",
+    "    random_scores = np.random.rand(len(sequence))\n",
+    "    result_str = \"\\n\".join(\n",
+    "        f\"{seq} {res.id[1]} {score:.2f}\" \n",
+    "        for seq, res, score in zip(sequence, chain, random_scores)\n",
+    "    )\n",
+    "    \n",
+    "    # Save the predictions to a file\n",
+    "    prediction_file = f\"{pdb_id}_predictions.txt\"\n",
+    "    with open(prediction_file, \"w\") as f:\n",
+    "        f.write(result_str)\n",
+    "    \n",
+    "    return result_str, molecule(pdb_path), prediction_file\n",
+    "\n",
+    "def molecule(input_pdb):\n",
+    "    mol = read_mol(input_pdb)  # Read PDB file content\n",
+    "    \n",
+    "    html_content = f\"\"\"\n",
+    "    <!DOCTYPE html>\n",
+    "    <html>\n",
+    "    <head>    \n",
+    "        <meta http-equiv=\"content-type\" content=\"text/html; charset=UTF-8\" />\n",
+    "        <style>\n",
+    "        .mol-container {{\n",
+    "            width: 100%;\n",
+    "            height: 700px;\n",
+    "            position: relative;\n",
+    "        }}\n",
+    "        </style>\n",
+    "        <script src=\"https://cdnjs.cloudflare.com/ajax/libs/jquery/3.6.3/jquery.min.js\"></script>\n",
+    "        <script src=\"https://3Dmol.csb.pitt.edu/build/3Dmol-min.js\"></script>\n",
+    "    </head>\n",
+    "    <body>\n",
+    "        <div id=\"container\" class=\"mol-container\"></div>\n",
+    "        <script>\n",
+    "            let pdb = `{mol}`; // Use template literal to properly escape PDB content\n",
+    "            $(document).ready(function () {{\n",
+    "                let element = $(\"#container\");\n",
+    "                let config = {{ backgroundColor: \"white\" }};\n",
+    "                let viewer = $3Dmol.createViewer(element, config);\n",
+    "                viewer.addModel(pdb, \"pdb\");\n",
+    "                \n",
+    "                // Set cartoon representation with white carbon color scheme\n",
+    "                viewer.getModel(0).setStyle({{}}, {{ cartoon: {{ colorscheme:\"whiteCarbon\" }} }});\n",
+    "                \n",
+    "                // Highlight specific histidine residues in red stick representation\n",
+    "                viewer.getModel(0).setStyle(\n",
+    "                    {{\"resn\": \"HIS\"}}, \n",
+    "                    {{\"stick\": {{\"color\": \"red\"}}}}\n",
+    "                );\n",
+    "                \n",
+    "                viewer.zoomTo();\n",
+    "                viewer.render();\n",
+    "                viewer.zoom(0.8, 2000);\n",
+    "            }});\n",
+    "        </script>\n",
+    "    </body>\n",
+    "    </html>\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    # Return the HTML content within an iframe safely encoded for special characters\n",
+    "    return f'<iframe width=\"100%\" height=\"700\" srcdoc=\"{html_content.replace(chr(34), \"&quot;\").replace(chr(39), \"&#39;\")}\"></iframe>'\n",
+    "\n",
+    "# Gradio UI\n",
+    "with gr.Blocks() as demo:\n",
+    "    gr.Markdown(\"# Protein Binding Site Prediction (Random Scores)\")\n",
+    "    with gr.Row():\n",
+    "        pdb_input = gr.Textbox(value=\"2IWI\", label=\"PDB ID\", placeholder=\"Enter PDB ID here...\")\n",
+    "        segment_input = gr.Textbox(value=\"A\", label=\"Chain ID\", placeholder=\"Enter Chain ID here...\")\n",
+    "        visualize_btn = gr.Button(\"Visualize Structure\")\n",
+    "        prediction_btn = gr.Button(\"Predict Random Binding Site Scores\")\n",
+    "    \n",
+    "    # Use HTML output instead of Molecule3D\n",
+    "    molecule_output = gr.HTML(label=\"Protein Structure\")\n",
+    "    predictions_output = gr.Textbox(label=\"Binding Site Predictions\")\n",
+    "    download_output = gr.File(label=\"Download Predictions\")\n",
+    "    \n",
+    "    visualize_btn.click(fetch_pdb, inputs=[pdb_input], outputs=molecule_output)\n",
+    "    prediction_btn.click(process_pdb, inputs=[pdb_input, segment_input], outputs=[predictions_output, molecule_output, download_output])\n",
+    "    \n",
+    "    gr.Markdown(\"## Examples\")\n",
+    "    gr.Examples(\n",
+    "        examples=[\n",
+    "            [\"2IWI\", \"A\"],\n",
+    "            [\"7RPZ\", \"B\"],\n",
+    "            [\"3TJN\", \"C\"]\n",
+    "        ],\n",
+    "        inputs=[pdb_input, segment_input],\n",
+    "        outputs=[predictions_output, molecule_output, download_output]\n",
+    "    )\n",
+    "\n",
+    "demo.launch(debug=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9a5facd9-855c-4b35-8dd3-2c0c8c7dd356",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "raw",
+   "id": "a762170f-92a9-473d-b18d-53607a780e3b",
+   "metadata": {},
+   "source": [
+    "import gradio as gr\n",
+    "import requests\n",
+    "from Bio.PDB import PDBParser\n",
+    "import numpy as np\n",
+    "import os\n",
+    "\n",
+    "def read_mol(pdb_path):\n",
+    "    \"\"\"Read PDB file and return its content as a string\"\"\"\n",
+    "    with open(pdb_path, 'r') as f:\n",
+    "        return f.read()\n",
+    "\n",
+    "# Function to fetch a PDB file from RCSB PDB\n",
+    "def fetch_pdb(pdb_id):\n",
+    "    pdb_url = f'https://files.rcsb.org/download/{pdb_id}.pdb'\n",
+    "    pdb_path = f'{pdb_id}.pdb'\n",
+    "    response = requests.get(pdb_url)\n",
+    "    if response.status_code == 200:\n",
+    "        with open(pdb_path, 'wb') as f:\n",
+    "            f.write(response.content)\n",
+    "        return pdb_path\n",
+    "    else:\n",
+    "        return None\n",
+    "\n",
+    "# Function to process the PDB file and return random predictions\n",
+    "def process_pdb(pdb_id, segment):\n",
+    "    pdb_path = fetch_pdb(pdb_id)\n",
+    "    if not pdb_path:\n",
+    "        return \"Failed to fetch PDB file\", None, None\n",
+    "    parser = PDBParser(QUIET=True)\n",
+    "    structure = parser.get_structure('protein', pdb_path)\n",
+    "    \n",
+    "    try:\n",
+    "        chain = structure[0][segment]\n",
+    "    except KeyError:\n",
+    "        return \"Invalid Chain ID\", None, None\n",
+    "    sequence = [residue.get_resname() for residue in chain if residue.id[0] == ' ']\n",
+    "    random_scores = np.random.rand(len(sequence))\n",
+    "    result_str = \"\\n\".join(\n",
+    "        f\"{seq} {res.id[1]} {score:.2f}\" \n",
+    "        for seq, res, score in zip(sequence, chain, random_scores)\n",
+    "    )\n",
+    "    # Save the predictions to a file\n",
+    "    prediction_file = f\"{pdb_id}_predictions.txt\"\n",
+    "    with open(prediction_file, \"w\") as f:\n",
+    "        f.write(result_str)\n",
+    "    \n",
+    "    return result_str, molecule(pdb_path), prediction_file\n",
+    "\n",
+    "def molecule(input_pdb):\n",
+    "    mol = read_mol(input_pdb)  # Read PDB file content\n",
+    "    \n",
+    "    html_content = f\"\"\"\n",
+    "    <!DOCTYPE html>\n",
+    "    <html>\n",
+    "    <head>    \n",
+    "        <meta http-equiv=\"content-type\" content=\"text/html; charset=UTF-8\" />\n",
+    "        <style>\n",
+    "        .mol-container {{\n",
+    "            width: 100%;\n",
+    "            height: 700px;\n",
+    "            position: relative;\n",
+    "        }}\n",
+    "        </style>\n",
+    "        <script src=\"https://cdnjs.cloudflare.com/ajax/libs/jquery/3.6.3/jquery.min.js\"></script>\n",
+    "        <script src=\"https://3Dmol.csb.pitt.edu/build/3Dmol-min.js\"></script>\n",
+    "    </head>\n",
+    "    <body>\n",
+    "        <div id=\"container\" class=\"mol-container\"></div>\n",
+    "        <script>\n",
+    "            let pdb = `{mol}`; // Use template literal to properly escape PDB content\n",
+    "            $(document).ready(function () {{\n",
+    "                let element = $(\"#container\");\n",
+    "                let config = {{ backgroundColor: \"white\" }};\n",
+    "                let viewer = $3Dmol.createViewer(element, config);\n",
+    "                viewer.addModel(pdb, \"pdb\");\n",
+    "                \n",
+    "                // Set cartoon representation with white carbon color scheme\n",
+    "                viewer.getModel(0).setStyle({{}}, {{ cartoon: {{ colorscheme:\"whiteCarbon\" }} }});\n",
+    "                \n",
+    "                // Highlight specific histidine residues in red stick representation\n",
+    "                viewer.getModel(0).setStyle(\n",
+    "                    {{\"resn\": \"HIS\"}}, \n",
+    "                    {{\"stick\": {{\"color\": \"red\"}}}}\n",
+    "                );\n",
+    "                \n",
+    "                viewer.zoomTo();\n",
+    "                viewer.render();\n",
+    "                viewer.zoom(0.8, 2000);\n",
+    "            }});\n",
+    "        </script>\n",
+    "    </body>\n",
+    "    </html>\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    # Return the HTML content within an iframe safely encoded for special characters\n",
+    "    return f'<iframe width=\"100%\" height=\"700\" srcdoc=\"{html_content.replace(chr(34), \"&quot;\").replace(chr(39), \"&#39;\")}\"></iframe>'\n",
+    "\n",
+    "# Gradio UI\n",
+    "with gr.Blocks() as demo:\n",
+    "    gr.Markdown(\"# Protein Binding Site Prediction (Random Scores)\")\n",
+    "    with gr.Row():\n",
+    "        pdb_input = gr.Textbox(value=\"2IWI\", label=\"PDB ID\", placeholder=\"Enter PDB ID here...\")\n",
+    "        segment_input = gr.Textbox(value=\"A\", label=\"Chain ID\", placeholder=\"Enter Chain ID here...\")\n",
+    "        visualize_btn = gr.Button(\"Visualize Structure\")\n",
+    "        prediction_btn = gr.Button(\"Predict Random Binding Site Scores\")\n",
+    "    \n",
+    "    molecule_output = gr.HTML(label=\"Protein Structure\")\n",
+    "    predictions_output = gr.Textbox(label=\"Binding Site Predictions\")\n",
+    "    download_output = gr.File(label=\"Download Predictions\")\n",
+    "    \n",
+    "    # Update to explicitly use molecule() function for visualization\n",
+    "    visualize_btn.click(\n",
+    "        fn=lambda pdb_id: molecule(fetch_pdb(pdb_id)), \n",
+    "        inputs=[pdb_input], \n",
+    "        outputs=molecule_output\n",
+    "    )\n",
+    "    \n",
+    "    prediction_btn.click(process_pdb, inputs=[pdb_input, segment_input], outputs=[predictions_output, molecule_output, download_output])\n",
+    "    \n",
+    "    gr.Markdown(\"## Examples\")\n",
+    "    gr.Examples(\n",
+    "        examples=[\n",
+    "            [\"2IWI\", \"A\"],\n",
+    "            [\"7RPZ\", \"B\"],\n",
+    "            [\"3TJN\", \"C\"]\n",
+    "        ],\n",
+    "        inputs=[pdb_input, segment_input],\n",
+    "        outputs=[predictions_output, molecule_output, download_output]\n",
+    "    )\n",
+    "\n",
+    "demo.launch()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "15527a58-c449-4da0-8fab-3baaede15e41",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9ef3e330-cb88-4c29-b84a-2f8652883cfc",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "* Running on local URL:  http://127.0.0.1:7867\n",
+      "* Running on local URL:  http://127.0.0.1:7860\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
@@ -266,7 +634,7 @@
     {
      "data": {
       "text/html": [
-       "<div><iframe src=\"http://127.0.0.1:7867/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+       "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -279,49 +647,24 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 8,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/tm/ym2tckv54b96ws82y3b7cqhh0000gn/T/ipykernel_11794/4072855226.py:39: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed in 3.11. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.\n",
-      "  colors = [cm.get_cmap('coolwarm')(score)[:3] for score in normalized_scores]\n",
-      "Traceback (most recent call last):\n",
-      "  File \"/Users/thorben_froehlking/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/queueing.py\", line 622, in process_events\n",
-      "    response = await route_utils.call_process_api(\n",
-      "               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/Users/thorben_froehlking/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/route_utils.py\", line 323, in call_process_api\n",
-      "    output = await app.get_blocks().process_api(\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/Users/thorben_froehlking/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/blocks.py\", line 2024, in process_api\n",
-      "    data = await self.postprocess_data(block_fn, result[\"prediction\"], state)\n",
-      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/Users/thorben_froehlking/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/blocks.py\", line 1830, in postprocess_data\n",
-      "    prediction_value = block.postprocess(prediction_value)\n",
-      "                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/Users/thorben_froehlking/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio_molecule3d/molecule3d.py\", line 210, in postprocess\n",
-      "    orig_name=Path(file).name,\n",
-      "              ^^^^^^^^^^\n",
-      "  File \"/Users/thorben_froehlking/anaconda3/envs/LLM/lib/python3.12/pathlib.py\", line 1162, in __init__\n",
-      "    super().__init__(*args)\n",
-      "  File \"/Users/thorben_froehlking/anaconda3/envs/LLM/lib/python3.12/pathlib.py\", line 373, in __init__\n",
-      "    raise TypeError(\n",
-      "TypeError: argument should be a str or an os.PathLike object where __fspath__ returns a str, not 'dict'\n"
-     ]
     }
    ],
    "source": [
     "import gradio as gr\n",
     "import requests\n",
     "from Bio.PDB import PDBParser\n",
-    "from gradio_molecule3d import Molecule3D\n",
     "import numpy as np\n",
-    "from matplotlib import cm\n",
+    "import os\n",
+    "from gradio_molecule3d import Molecule3D\n",
+    "\n",
+    "def read_mol(pdb_path):\n",
+    "    \"\"\"Read PDB file and return its content as a string\"\"\"\n",
+    "    with open(pdb_path, 'r') as f:\n",
+    "        return f.read()\n",
     "\n",
-    "# Function to fetch a PDB file from RCSB PDB\n",
     "def fetch_pdb(pdb_id):\n",
     "    pdb_url = f'https://files.rcsb.org/download/{pdb_id}.pdb'\n",
     "    pdb_path = f'{pdb_id}.pdb'\n",
@@ -333,78 +676,129 @@
     "    else:\n",
     "        return None\n",
     "\n",
-    "# Function to process the PDB file and return random predictions\n",
     "def process_pdb(pdb_id, segment):\n",
     "    pdb_path = fetch_pdb(pdb_id)\n",
     "    if not pdb_path:\n",
-    "        return \"Failed to fetch PDB file\", None, None, None\n",
-    "\n",
+    "        return \"Failed to fetch PDB file\", None, None\n",
     "    parser = PDBParser(QUIET=True)\n",
     "    structure = parser.get_structure('protein', pdb_path)\n",
-    "\n",
+    "    \n",
     "    try:\n",
     "        chain = structure[0][segment]\n",
     "    except KeyError:\n",
-    "        return \"Invalid Chain ID\", None, None, None\n",
-    "\n",
+    "        return \"Invalid Chain ID\", None, None\n",
     "    sequence = [residue.get_resname() for residue in chain if residue.id[0] == ' ']\n",
     "    random_scores = np.random.rand(len(sequence))\n",
-    "\n",
-    "    # Normalize scores for coloring (0 = blue, 1 = red)\n",
-    "    normalized_scores = (random_scores - np.min(random_scores)) / (np.max(random_scores) - np.min(random_scores))\n",
-    "    colors = [cm.get_cmap('coolwarm')(score)[:3] for score in normalized_scores]\n",
-    "    hex_colors = [f'#{int(r*255):02x}{int(g*255):02x}{int(b*255):02x}' for r, g, b in colors]\n",
-    "\n",
-    "    # Result string and representation\n",
     "    result_str = \"\\n\".join(\n",
     "        f\"{seq} {res.id[1]} {score:.2f}\" \n",
     "        for seq, res, score in zip(sequence, chain, random_scores)\n",
     "    )\n",
-    "\n",
-    "    # Representation for the protein structure\n",
-    "    reps = [\n",
-    "        {\n",
-    "            \"model\": 0,\n",
-    "            \"style\": \"cartoon\",\n",
-    "            \"color\": \"whiteCarbon\"\n",
-    "        }\n",
-    "    ] + [\n",
-    "        {\n",
-    "            \"model\": 0,\n",
-    "            \"style\": \"cartoon\",\n",
-    "            \"residue_index\": i,\n",
-    "            \"color\": color\n",
-    "        }\n",
-    "        for i, color in enumerate(hex_colors)\n",
-    "    ]\n",
-    "\n",
     "    # Save the predictions to a file\n",
     "    prediction_file = f\"{pdb_id}_predictions.txt\"\n",
     "    with open(prediction_file, \"w\") as f:\n",
     "        f.write(result_str)\n",
     "    \n",
-    "    return result_str, reps, prediction_file\n",
+    "    return result_str, molecule(pdb_path, random_scores), prediction_file\n",
     "\n",
+    "def molecule(input_pdb, scores=None):\n",
+    "    mol = read_mol(input_pdb)  # Read PDB file content\n",
+    "    \n",
+    "    # Prepare high-scoring residues script if scores are provided\n",
+    "    high_score_script = \"\"\n",
+    "    if scores is not None:\n",
+    "        high_score_script = \"\"\"\n",
+    "        // Highlight residues with high scores\n",
+    "        let highScoreResidues = [{}];\n",
+    "        viewer.getModel(0).setStyle(\n",
+    "            {{\"resi\": highScoreResidues}}, \n",
+    "            {{\"stick\": {{\"color\": \"red\"}}}}\n",
+    "        );\n",
+    "        \"\"\".format(\n",
+    "            \", \".join(str(i+1) for i, score in enumerate(scores) if score > 0.8)\n",
+    "        )\n",
+    "    \n",
+    "    html_content = f\"\"\"\n",
+    "    <!DOCTYPE html>\n",
+    "    <html>\n",
+    "    <head>    \n",
+    "        <meta http-equiv=\"content-type\" content=\"text/html; charset=UTF-8\" />\n",
+    "        <style>\n",
+    "        .mol-container {{\n",
+    "            width: 100%;\n",
+    "            height: 700px;\n",
+    "            position: relative;\n",
+    "        }}\n",
+    "        </style>\n",
+    "        <script src=\"https://cdnjs.cloudflare.com/ajax/libs/jquery/3.6.3/jquery.min.js\"></script>\n",
+    "        <script src=\"https://3Dmol.csb.pitt.edu/build/3Dmol-min.js\"></script>\n",
+    "    </head>\n",
+    "    <body>\n",
+    "        <div id=\"container\" class=\"mol-container\"></div>\n",
+    "        <script>\n",
+    "            let pdb = `{mol}`; // Use template literal to properly escape PDB content\n",
+    "            $(document).ready(function () {{\n",
+    "                let element = $(\"#container\");\n",
+    "                let config = {{ backgroundColor: \"white\" }};\n",
+    "                let viewer = $3Dmol.createViewer(element, config);\n",
+    "                viewer.addModel(pdb, \"pdb\");\n",
+    "                \n",
+    "                // Set cartoon representation with white carbon color scheme\n",
+    "                viewer.getModel(0).setStyle({{}}, {{ cartoon: {{ colorscheme:\"whiteCarbon\" }} }});\n",
+    "                \n",
+    "                {high_score_script}\n",
+    "                \n",
+    "                viewer.zoomTo();\n",
+    "                viewer.render();\n",
+    "                viewer.zoom(0.8, 2000);\n",
+    "            }});\n",
+    "        </script>\n",
+    "    </body>\n",
+    "    </html>\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    # Return the HTML content within an iframe safely encoded for special characters\n",
+    "    return f'<iframe width=\"100%\" height=\"700\" srcdoc=\"{html_content.replace(chr(34), \"&quot;\").replace(chr(39), \"&#39;\")}\"></iframe>'\n",
+    "\n",
+    "reps =    [\n",
+    "        {\n",
+    "          \"model\": 0,\n",
+    "          \"style\": \"cartoon\",\n",
+    "          \"color\": \"whiteCarbon\",\n",
+    "          \"residue_range\": \"\",\n",
+    "          \"around\": 0,\n",
+    "          \"byres\": False,\n",
+    "        }\n",
+    "    ]\n",
     "# Gradio UI\n",
     "with gr.Blocks() as demo:\n",
     "    gr.Markdown(\"# Protein Binding Site Prediction (Random Scores)\")\n",
-    "\n",
     "    with gr.Row():\n",
     "        pdb_input = gr.Textbox(value=\"2IWI\", label=\"PDB ID\", placeholder=\"Enter PDB ID here...\")\n",
     "        segment_input = gr.Textbox(value=\"A\", label=\"Chain ID\", placeholder=\"Enter Chain ID here...\")\n",
     "        visualize_btn = gr.Button(\"Visualize Structure\")\n",
+    "        #prediction_btn = gr.Button(\"Predict Random Binding Site Scores\")\n",
+    "\n",
+    "    molecule_output2 = Molecule3D(label=\"Protein Structure\", reps=reps)\n",
+    "\n",
+    "    with gr.Row():\n",
+    "        pdb_input = gr.Textbox(value=\"2IWI\", label=\"PDB ID\", placeholder=\"Enter PDB ID here...\")\n",
+    "        segment_input = gr.Textbox(value=\"A\", label=\"Chain ID\", placeholder=\"Enter Chain ID here...\")\n",
     "        prediction_btn = gr.Button(\"Predict Random Binding Site Scores\")\n",
     "\n",
-    "    molecule_output = Molecule3D(label=\"Protein Structure\", reps=reps)\n",
+    "    molecule_output = gr.HTML(label=\"Protein Structure\")\n",
     "    predictions_output = gr.Textbox(label=\"Binding Site Predictions\")\n",
     "    download_output = gr.File(label=\"Download Predictions\")\n",
-    "\n",
-    "    prediction_btn.click(\n",
-    "        fn=process_pdb,\n",
-    "        inputs=[pdb_input, segment_input],\n",
-    "        outputs=[predictions_output, molecule_output, download_output]\n",
-    "    )\n",
-    "\n",
+    "    \n",
+    "    #visualize_btn.click(\n",
+    "    #    fn=lambda pdb_id: molecule(fetch_pdb(pdb_id)), \n",
+    "    #    inputs=[pdb_input], \n",
+    "    #    outputs=molecule_output\n",
+    "    #)\n",
+    "    visualize_btn.click(fetch_pdb, inputs=[pdb_input], outputs=molecule_output2)\n",
+    "    \n",
+    "    \n",
+    "    prediction_btn.click(process_pdb, inputs=[pdb_input, segment_input], outputs=[predictions_output, molecule_output, download_output])\n",
+    "    \n",
     "    gr.Markdown(\"## Examples\")\n",
     "    gr.Examples(\n",
     "        examples=[\n",
@@ -422,7 +816,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ee215c16-a1fb-450f-bb93-37aaee6fb3f1",
+   "id": "14605615-8610-4d9e-841b-db7618cde844",
    "metadata": {},
    "outputs": [],
    "source": []

.ipynb_checkpoints/test2-checkpoint.ipynb

@@ -978,7 +978,7 @@
     "        examples=[\n",
     "            [\"7RPZ\", \"A\"],\n",
     "            [\"2IWI\", \"B\"],\n",
-    "            [\"3TJN\", \"C\"]\n",
+    "            [\"2F6V\", \"A\"]\n",
     "        ],\n",
     "        inputs=[pdb_input, segment_input],\n",
     "        outputs=[predictions_output, molecule_output, download_output]\n",
@@ -1279,7 +1279,7 @@
     "        examples=[\n",
     "            [\"7RPZ\", \"A\"],\n",
     "            [\"2IWI\", \"B\"],\n",
-    "            [\"3TJN\", \"C\"]\n",
+    "            [\"2F6V\", \"A\"]\n",
     "        ],\n",
     "        inputs=[pdb_input, segment_input],\n",
     "        outputs=[predictions_output, molecule_output, download_output]\n",
@@ -1387,6 +1387,10 @@
     "        for residue in chain \n",
     "        if residue.get_resname().strip() in aa_dict\n",
     "    )\n",
+    "    sequence2 = [\n",
+    "        (res.id[1], res) for res in chain\n",
+    "        if res.get_resname().strip() in aa_dict\n",
+    "    ]\n",
     "    \n",
     "    # Prepare input for model prediction\n",
     "    input_ids = tokenizer(\" \".join(sequence), return_tensors=\"pt\").input_ids.to(device)\n",
@@ -1397,6 +1401,9 @@
     "    scores = expit(outputs[:, 1] - outputs[:, 0])\n",
     "    normalized_scores = normalize_scores(scores)\n",
     "\n",
+    "    # Zip residues with scores to track the residue ID and score\n",
+    "    residue_scores = [(resi, score) for (resi, _), score in zip(sequence2, normalized_scores)]\n",
+    "    \n",
     "    result_str = \"\\n\".join([\n",
     "        f\"{res.get_resname()} {res.id[1]} {sequence[i]} {normalized_scores[i]:.2f}\" \n",
     "        for i, res in enumerate(chain) if res.get_resname().strip() in aa_dict\n",
@@ -1407,14 +1414,18 @@
     "    with open(prediction_file, \"w\") as f:\n",
     "        f.write(result_str)\n",
     "    \n",
-    "    return result_str, molecule(pdb_path, normalized_scores, segment), prediction_file\n",
+    "    return result_str, molecule(pdb_path, residue_scores, segment), prediction_file\n",
     "\n",
-    "def molecule(input_pdb, scores=None, segment='A'):\n",
+    "def molecule(input_pdb, residue_scores=None, segment='A'):\n",
     "    mol = read_mol(input_pdb)  # Read PDB file content\n",
     "    \n",
     "    # Prepare high-scoring residues script if scores are provided\n",
     "    high_score_script = \"\"\n",
-    "    if scores is not None:\n",
+    "    if residue_scores is not None:\n",
+    "        # Sort residues based on their scores\n",
+    "        high_score_residues = [resi for resi, score in residue_scores if score > 0.75]\n",
+    "        mid_score_residues = [resi for resi, score in residue_scores if 0.5 < score <= 0.75]\n",
+    "        \n",
     "        high_score_script = \"\"\"\n",
     "        // Reset all styles first\n",
     "        viewer.getModel(0).setStyle({}, {});\n",
@@ -1432,16 +1443,16 @@
     "            {\"stick\": {\"color\": \"red\"}}\n",
     "        );\n",
     "\n",
-    "        // Highlight high-scoring residues only for the selected chain\n",
-    "        let highScoreResidues2 = [%s];\n",
+    "        // Highlight medium-scoring residues only for the selected chain\n",
+    "        let midScoreResidues = [%s];\n",
     "        viewer.getModel(0).setStyle(\n",
-    "            {\"chain\": \"%s\", \"resi\": highScoreResidues2}, \n",
+    "            {\"chain\": \"%s\", \"resi\": midScoreResidues}, \n",
     "            {\"stick\": {\"color\": \"orange\"}}\n",
     "        );\n",
     "        \"\"\" % (segment, \n",
-    "               \", \".join(str(i+1) for i, score in enumerate(scores) if score > 0.8),\n",
+    "               \", \".join(str(resi) for resi in high_score_residues),\n",
     "               segment,\n",
-    "              \", \".join(str(i+1) for i, score in enumerate(scores) if (score > 0.5) and (score < 0.8)),\n",
+    "               \", \".join(str(resi) for resi in mid_score_residues),\n",
     "               segment)\n",
     "    \n",
     "    html_content = f\"\"\"\n",
@@ -1484,7 +1495,7 @@
     "                    function(atom, viewer, event, container) {{\n",
     "                        if (!atom.label) {{\n",
     "                            atom.label = viewer.addLabel(\n",
-    "                                atom.resn + \":\" + atom.atom, \n",
+    "                                atom.resn + \":\" +atom.resi + \":\" + atom.atom, \n",
     "                                {{\n",
     "                                    position: atom, \n",
     "                                    backgroundColor: 'mintcream', \n",
@@ -1528,7 +1539,7 @@
     "\n",
     "# Gradio UI\n",
     "with gr.Blocks() as demo:\n",
-    "    gr.Markdown(\"# Protein Binding Site Prediction (Random Scores)\")\n",
+    "    gr.Markdown(\"# Protein Binding Site Prediction\")\n",
     "    with gr.Row():\n",
     "        pdb_input = gr.Textbox(value=\"2IWI\", label=\"PDB ID\", placeholder=\"Enter PDB ID here...\")\n",
     "        visualize_btn = gr.Button(\"Visualize Structure\")\n",
@@ -1536,9 +1547,9 @@
     "    molecule_output2 = Molecule3D(label=\"Protein Structure\", reps=reps)\n",
     "\n",
     "    with gr.Row():\n",
-    "        pdb_input = gr.Textbox(value=\"2IWI\", label=\"PDB ID\", placeholder=\"Enter PDB ID here...\")\n",
+    "        #pdb_input = gr.Textbox(value=\"2IWI\", label=\"PDB ID\", placeholder=\"Enter PDB ID here...\")\n",
     "        segment_input = gr.Textbox(value=\"A\", label=\"Chain ID\", placeholder=\"Enter Chain ID here...\")\n",
-    "        prediction_btn = gr.Button(\"Predict Random Binding Site Scores\")\n",
+    "        prediction_btn = gr.Button(\"Predict Binding Site\")\n",
     "\n",
     "    molecule_output = gr.HTML(label=\"Protein Structure\")\n",
     "    predictions_output = gr.Textbox(label=\"Binding Site Predictions\")\n",
@@ -1551,9 +1562,9 @@
     "    gr.Markdown(\"## Examples\")\n",
     "    gr.Examples(\n",
     "        examples=[\n",
-    "            [\"2IWI\", \"A\"],\n",
-    "            [\"7RPZ\", \"B\"],\n",
-    "            [\"3TJN\", \"C\"]\n",
+    "            [\"7RPZ\", \"A\"],\n",
+    "            [\"2IWI\", \"B\"],\n",
+    "            [\"2F6V\", \"A\"]\n",
     "        ],\n",
     "        inputs=[pdb_input, segment_input],\n",
     "        outputs=[predictions_output, molecule_output, download_output]\n",

app.py

@@ -234,7 +234,7 @@ reps =    [
 
 # Gradio UI
 with gr.Blocks() as demo:
-    gr.Markdown("# Protein Binding Site Prediction (Random Scores)")
+    gr.Markdown("# Protein Binding Site Prediction")
     with gr.Row():
         pdb_input = gr.Textbox(value="2IWI", label="PDB ID", placeholder="Enter PDB ID here...")
         visualize_btn = gr.Button("Visualize Structure")
@@ -244,7 +244,7 @@ with gr.Blocks() as demo:
     with gr.Row():
         #pdb_input = gr.Textbox(value="2IWI", label="PDB ID", placeholder="Enter PDB ID here...")
         segment_input = gr.Textbox(value="A", label="Chain ID", placeholder="Enter Chain ID here...")
-        prediction_btn = gr.Button("Predict Random Binding Site Scores")
+        prediction_btn = gr.Button("Predict Binding Site")
 
     molecule_output = gr.HTML(label="Protein Structure")
     predictions_output = gr.Textbox(label="Binding Site Predictions")

test2.ipynb

@@ -978,7 +978,7 @@
     "        examples=[\n",
     "            [\"7RPZ\", \"A\"],\n",
     "            [\"2IWI\", \"B\"],\n",
-    "            [\"3TJN\", \"C\"]\n",
+    "            [\"2F6V\", \"A\"]\n",
     "        ],\n",
     "        inputs=[pdb_input, segment_input],\n",
     "        outputs=[predictions_output, molecule_output, download_output]\n",
@@ -1279,7 +1279,7 @@
     "        examples=[\n",
     "            [\"7RPZ\", \"A\"],\n",
     "            [\"2IWI\", \"B\"],\n",
-    "            [\"3TJN\", \"C\"]\n",
+    "            [\"2F6V\", \"A\"]\n",
     "        ],\n",
     "        inputs=[pdb_input, segment_input],\n",
     "        outputs=[predictions_output, molecule_output, download_output]\n",
@@ -1387,6 +1387,10 @@
     "        for residue in chain \n",
     "        if residue.get_resname().strip() in aa_dict\n",
     "    )\n",
+    "    sequence2 = [\n",
+    "        (res.id[1], res) for res in chain\n",
+    "        if res.get_resname().strip() in aa_dict\n",
+    "    ]\n",
     "    \n",
     "    # Prepare input for model prediction\n",
     "    input_ids = tokenizer(\" \".join(sequence), return_tensors=\"pt\").input_ids.to(device)\n",
@@ -1397,6 +1401,9 @@
     "    scores = expit(outputs[:, 1] - outputs[:, 0])\n",
     "    normalized_scores = normalize_scores(scores)\n",
     "\n",
+    "    # Zip residues with scores to track the residue ID and score\n",
+    "    residue_scores = [(resi, score) for (resi, _), score in zip(sequence2, normalized_scores)]\n",
+    "    \n",
     "    result_str = \"\\n\".join([\n",
     "        f\"{res.get_resname()} {res.id[1]} {sequence[i]} {normalized_scores[i]:.2f}\" \n",
     "        for i, res in enumerate(chain) if res.get_resname().strip() in aa_dict\n",
@@ -1407,14 +1414,18 @@
     "    with open(prediction_file, \"w\") as f:\n",
     "        f.write(result_str)\n",
     "    \n",
-    "    return result_str, molecule(pdb_path, normalized_scores, segment), prediction_file\n",
+    "    return result_str, molecule(pdb_path, residue_scores, segment), prediction_file\n",
     "\n",
-    "def molecule(input_pdb, scores=None, segment='A'):\n",
+    "def molecule(input_pdb, residue_scores=None, segment='A'):\n",
     "    mol = read_mol(input_pdb)  # Read PDB file content\n",
     "    \n",
     "    # Prepare high-scoring residues script if scores are provided\n",
     "    high_score_script = \"\"\n",
-    "    if scores is not None:\n",
+    "    if residue_scores is not None:\n",
+    "        # Sort residues based on their scores\n",
+    "        high_score_residues = [resi for resi, score in residue_scores if score > 0.75]\n",
+    "        mid_score_residues = [resi for resi, score in residue_scores if 0.5 < score <= 0.75]\n",
+    "        \n",
     "        high_score_script = \"\"\"\n",
     "        // Reset all styles first\n",
     "        viewer.getModel(0).setStyle({}, {});\n",
@@ -1432,16 +1443,16 @@
     "            {\"stick\": {\"color\": \"red\"}}\n",
     "        );\n",
     "\n",
-    "        // Highlight high-scoring residues only for the selected chain\n",
-    "        let highScoreResidues2 = [%s];\n",
+    "        // Highlight medium-scoring residues only for the selected chain\n",
+    "        let midScoreResidues = [%s];\n",
     "        viewer.getModel(0).setStyle(\n",
-    "            {\"chain\": \"%s\", \"resi\": highScoreResidues2}, \n",
+    "            {\"chain\": \"%s\", \"resi\": midScoreResidues}, \n",
     "            {\"stick\": {\"color\": \"orange\"}}\n",
     "        );\n",
     "        \"\"\" % (segment, \n",
-    "               \", \".join(str(i+1) for i, score in enumerate(scores) if score > 0.8),\n",
+    "               \", \".join(str(resi) for resi in high_score_residues),\n",
     "               segment,\n",
-    "              \", \".join(str(i+1) for i, score in enumerate(scores) if (score > 0.5) and (score < 0.8)),\n",
+    "               \", \".join(str(resi) for resi in mid_score_residues),\n",
     "               segment)\n",
     "    \n",
     "    html_content = f\"\"\"\n",
@@ -1484,7 +1495,7 @@
     "                    function(atom, viewer, event, container) {{\n",
     "                        if (!atom.label) {{\n",
     "                            atom.label = viewer.addLabel(\n",
-    "                                atom.resn + \":\" + atom.atom, \n",
+    "                                atom.resn + \":\" +atom.resi + \":\" + atom.atom, \n",
     "                                {{\n",
     "                                    position: atom, \n",
     "                                    backgroundColor: 'mintcream', \n",
@@ -1528,7 +1539,7 @@
     "\n",
     "# Gradio UI\n",
     "with gr.Blocks() as demo:\n",
-    "    gr.Markdown(\"# Protein Binding Site Prediction (Random Scores)\")\n",
+    "    gr.Markdown(\"# Protein Binding Site Prediction\")\n",
     "    with gr.Row():\n",
     "        pdb_input = gr.Textbox(value=\"2IWI\", label=\"PDB ID\", placeholder=\"Enter PDB ID here...\")\n",
     "        visualize_btn = gr.Button(\"Visualize Structure\")\n",
@@ -1536,9 +1547,9 @@
     "    molecule_output2 = Molecule3D(label=\"Protein Structure\", reps=reps)\n",
     "\n",
     "    with gr.Row():\n",
-    "        pdb_input = gr.Textbox(value=\"2IWI\", label=\"PDB ID\", placeholder=\"Enter PDB ID here...\")\n",
+    "        #pdb_input = gr.Textbox(value=\"2IWI\", label=\"PDB ID\", placeholder=\"Enter PDB ID here...\")\n",
     "        segment_input = gr.Textbox(value=\"A\", label=\"Chain ID\", placeholder=\"Enter Chain ID here...\")\n",
-    "        prediction_btn = gr.Button(\"Predict Random Binding Site Scores\")\n",
+    "        prediction_btn = gr.Button(\"Predict Binding Site\")\n",
     "\n",
     "    molecule_output = gr.HTML(label=\"Protein Structure\")\n",
     "    predictions_output = gr.Textbox(label=\"Binding Site Predictions\")\n",
@@ -1551,9 +1562,9 @@
     "    gr.Markdown(\"## Examples\")\n",
     "    gr.Examples(\n",
     "        examples=[\n",
-    "            [\"2IWI\", \"A\"],\n",
-    "            [\"7RPZ\", \"B\"],\n",
-    "            [\"3TJN\", \"C\"]\n",
+    "            [\"7RPZ\", \"A\"],\n",
+    "            [\"2IWI\", \"B\"],\n",
+    "            [\"2F6V\", \"A\"]\n",
     "        ],\n",
     "        inputs=[pdb_input, segment_input],\n",
     "        outputs=[predictions_output, molecule_output, download_output]\n",