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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"id": "1f8ea359-674c-4263-9c2a-7a8e7e464249",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"* Running on local URL: http://127.0.0.1:7862\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
"<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>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"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",
"\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",
"\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",
"\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, pdb_path, prediction_file\n",
"\n",
"#reps = [{\"model\": 0, \"style\": \"cartoon\", \"color\": \"spectrum\"}]\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",
" \"model\": 0,\n",
" \"chain\": \"A\",\n",
" \"resname\": \"HIS\",\n",
" \"style\": \"stick\",\n",
" \"color\": \"red\"\n",
" }\n",
" ]\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_output = Molecule3D(label=\"Protein Structure\", reps=reps)\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()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bd50ff2e-ed03-498e-8af2-73c0fb8ea07e",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "raw",
"id": "88affe12-7c48-4bd6-9e46-32cdffa729fe",
"metadata": {},
"source": [
"import gradio as gr\n",
"from gradio_molecule3d import Molecule3D\n",
"\n",
"\n",
"example = Molecule3D().example_value()\n",
"\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",
" \"model\": 0,\n",
" \"chain\": \"A\",\n",
" \"resname\": \"HIS\",\n",
" \"style\": \"stick\",\n",
" \"color\": \"red\"\n",
" }\n",
" ]\n",
"\n",
"\n",
"\n",
"def predict(x):\n",
" print(\"predict function\", x)\n",
" print(x.name)\n",
" return x\n",
"\n",
"with gr.Blocks() as demo:\n",
" gr.Markdown(\"# Molecule3D\")\n",
" inp = Molecule3D(label=\"Molecule3D\", reps=reps)\n",
" out = Molecule3D(label=\"Output\", reps=reps)\n",
"\n",
" btn = gr.Button(\"Predict\")\n",
" gr.Markdown(\"\"\" \n",
" You can configure the default rendering of the molecule by adding a list of representations\n",
" <pre>\n",
" reps = [\n",
" {\n",
" \"model\": 0,\n",
" \"style\": \"cartoon\",\n",
" \"color\": \"whiteCarbon\",\n",
" \"residue_range\": \"\",\n",
" \"around\": 0,\n",
" \"byres\": False,\n",
" },\n",
" {\n",
" \"model\": 0,\n",
" \"chain\": \"A\",\n",
" \"resname\": \"HIS\",\n",
" \"style\": \"stick\",\n",
" \"color\": \"red\"\n",
" }\n",
" ]\n",
" </pre>\n",
" \"\"\")\n",
" btn.click(predict, inputs=inp, outputs=out)\n",
"\n",
"\n",
"if __name__ == \"__main__\":\n",
" demo.launch()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d27cc368-26a0-42c2-a68a-8833de7bb4a0",
"metadata": {},
"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), \""\").replace(chr(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": 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), \""\").replace(chr(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), \""\").replace(chr(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://127.0.0.1:7860\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
"<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>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import gradio as gr\n",
"import requests\n",
"from Bio.PDB import PDBParser\n",
"import numpy as np\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",
"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",
"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, 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), \""\").replace(chr(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",
" 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 = 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(\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",
" [\"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": "14605615-8610-4d9e-841b-db7618cde844",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (LLM)",
"language": "python",
"name": "llm"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.7"
}
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"nbformat": 4,
"nbformat_minor": 5
}
|