Updated

.gradio/cached_examples/43/log.csv

@@ -0,0 +1,4 @@
+PyMOL Visualization Commands,Interactive 3D Structure,Download Results,component 3,timestamp
+Failed to create chain-specific PDB: invalid literal for int() with base 10: 'THR',,,"{'visible': False, '__type__': 'update'}",2025-04-09 13:42:40.355486
+Failed to create chain-specific PDB: invalid literal for int() with base 10: 'YR',,,"{'visible': False, '__type__': 'update'}",2025-04-09 13:42:41.822673
+Failed to create chain-specific PDB: invalid literal for int() with base 10: 'LU',,,"{'visible': False, '__type__': 'update'}",2025-04-09 13:42:43.191727

.ipynb_checkpoints/app-checkpoint.py

@@ -30,7 +30,8 @@ from scipy.special import expit
 
 # Load model and move to device
 #checkpoint = 'ThorbenF/prot_t5_xl_uniref50'
-checkpoint = 'ThorbenF/prot_t5_xl_uniref50_cryptic'
+#checkpoint = 'ThorbenF/prot_t5_xl_uniref50_cryptic'
+checkpoint = 'ThorbenF/prot_t5_xl_uniref50_database'
 max_length = 1500
 model, tokenizer = load_model(checkpoint, max_length)
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
@@ -445,7 +446,7 @@ with gr.Blocks(css="""
             "color": "whiteCarbon",
             "residue_range": "",
             "around": 0,
-            "byres": False,
+            #"byres": False,
         }
     ])
 
@@ -532,4 +533,4 @@ with gr.Blocks(css="""
         outputs=[predictions_output, molecule_output, download_output]
     )
 
-demo.launch(share=True)
+demo.launch(share=True)

app.py

@@ -446,7 +446,7 @@ with gr.Blocks(css="""
             "color": "whiteCarbon",
             "residue_range": "",
             "around": 0,
-            "byres": False,
+            #"byres": False,
         }
     ])
 

app.py.backup

@@ -1,542 +0,0 @@
-from datetime import datetime
-import gradio as gr
-import requests
-from Bio.PDB import PDBParser, MMCIFParser, PDBIO, Select
-from Bio.PDB.Polypeptide import is_aa
-from Bio.SeqUtils import seq1
-from typing import Optional, Tuple
-import numpy as np
-import os
-from gradio_molecule3d import Molecule3D
-
-from model_loader import load_model
-
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-from torch.utils.data import DataLoader
-
-import re
-import pandas as pd
-import copy
-
-import transformers
-from transformers import AutoTokenizer, DataCollatorForTokenClassification
-
-from datasets import Dataset
-
-from scipy.special import expit
-
-
-# Load model and move to device
-checkpoint = 'ThorbenF/prot_t5_xl_uniref50'
-max_length = 1500
-model, tokenizer = load_model(checkpoint, max_length)
-device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-model.to(device)
-model.eval()
-
-def normalize_scores(scores):
-    min_score = np.min(scores)
-    max_score = np.max(scores)
-    return (scores - min_score) / (max_score - min_score) if max_score > min_score else scores
-
-def read_mol(pdb_path):
-    """Read PDB file and return its content as a string"""
-    with open(pdb_path, 'r') as f:
-        return f.read()
-
-def fetch_structure(pdb_id: str, output_dir: str = ".") -> Optional[str]:
-    """
-    Fetch the structure file for a given PDB ID. Prioritizes CIF files.
-    If a structure file already exists locally, it uses that.
-    """
-    file_path = download_structure(pdb_id, output_dir)
-    if file_path:
-        return file_path
-    else:
-        return None
-
-def download_structure(pdb_id: str, output_dir: str) -> Optional[str]:
-    """
-    Attempt to download the structure file in CIF or PDB format.
-    Returns the path to the downloaded file, or None if download fails.
-    """
-    for ext in ['.cif', '.pdb']:
-        file_path = os.path.join(output_dir, f"{pdb_id}{ext}")
-        if os.path.exists(file_path):
-            return file_path
-        url = f"https://files.rcsb.org/download/{pdb_id}{ext}"
-        try:
-            response = requests.get(url, timeout=10)
-            if response.status_code == 200:
-                with open(file_path, 'wb') as f:
-                    f.write(response.content)
-                return file_path
-        except Exception as e:
-            print(f"Download error for {pdb_id}{ext}: {e}")
-    return None
-
-def convert_cif_to_pdb(cif_path: str, output_dir: str = ".") -> str:
-    """
-    Convert a CIF file to PDB format using BioPython and return the PDB file path.
-    """
-    pdb_path = os.path.join(output_dir, os.path.basename(cif_path).replace('.cif', '.pdb'))
-    parser = MMCIFParser(QUIET=True)
-    structure = parser.get_structure('protein', cif_path)
-    io = PDBIO()
-    io.set_structure(structure)
-    io.save(pdb_path)
-    return pdb_path
-
-def fetch_pdb(pdb_id):
-    pdb_path = fetch_structure(pdb_id)
-    if not pdb_path:
-        return None
-    _, ext = os.path.splitext(pdb_path)
-    if ext == '.cif':
-        pdb_path = convert_cif_to_pdb(pdb_path)
-    return pdb_path
-
-def create_chain_specific_pdb(input_pdb: str, chain_id: str, residue_scores: list, protein_residues: list) -> str:
-    """
-    Create a PDB file with only the selected chain and residues, replacing B-factor with prediction scores
-    """
-    # Read the original PDB file
-    parser = PDBParser(QUIET=True)
-    structure = parser.get_structure('protein', input_pdb)
-    
-    # Prepare a new structure with only the specified chain and selected residues
-    output_pdb = f"{os.path.splitext(input_pdb)[0]}_{chain_id}_predictions_scores.pdb"
-    
-    # Create scores dictionary for easy lookup
-    scores_dict = {resi: score for resi, score in residue_scores}
-
-    # Create a custom Select class
-    class ResidueSelector(Select):
-        def __init__(self, chain_id, selected_residues, scores_dict):
-            self.chain_id = chain_id
-            self.selected_residues = selected_residues
-            self.scores_dict = scores_dict
-        
-        def accept_chain(self, chain):
-            return chain.id == self.chain_id
-        
-        def accept_residue(self, residue):
-            return residue.id[1] in self.selected_residues
-
-        def accept_atom(self, atom):
-            if atom.parent.id[1] in self.scores_dict:
-                atom.bfactor = np.absolute(1-self.scores_dict[atom.parent.id[1]]) * 100
-            return True
-
-    # Prepare output PDB with selected chain and residues, modified B-factors
-    io = PDBIO()
-    selector = ResidueSelector(chain_id, [res.id[1] for res in protein_residues], scores_dict)
-    
-    io.set_structure(structure[0])
-    io.save(output_pdb, selector)
-    
-    return output_pdb
-
-def calculate_geometric_center(pdb_path: str, high_score_residues: list, chain_id: str):
-    """
-    Calculate the geometric center of high-scoring residues
-    """
-    parser = PDBParser(QUIET=True)
-    structure = parser.get_structure('protein', pdb_path)
-    
-    # Collect coordinates of CA atoms from high-scoring residues
-    coords = []
-    for model in structure:
-        for chain in model:
-            if chain.id == chain_id:
-                for residue in chain:
-                    if residue.id[1] in high_score_residues:
-                        if 'CA' in residue:  # Use alpha carbon as representative
-                            ca_atom = residue['CA']
-                            coords.append(ca_atom.coord)
-    
-    # Calculate geometric center
-    if coords:
-        center = np.mean(coords, axis=0)
-        return center
-    return None
-
-def process_pdb(pdb_id_or_file, segment):
-    # Determine if input is a PDB ID or file path
-    if pdb_id_or_file.endswith('.pdb'):
-        pdb_path = pdb_id_or_file
-        pdb_id = os.path.splitext(os.path.basename(pdb_path))[0]
-    else:
-        pdb_id = pdb_id_or_file
-        pdb_path = fetch_pdb(pdb_id)
-    
-    if not pdb_path:
-        return "Failed to fetch PDB file", None, None
-    
-    # Determine the file format and choose the appropriate parser
-    _, ext = os.path.splitext(pdb_path)
-    parser = MMCIFParser(QUIET=True) if ext == '.cif' else PDBParser(QUIET=True)
-    
-    try:
-        # Parse the structure file
-        structure = parser.get_structure('protein', pdb_path)
-    except Exception as e:
-        return f"Error parsing structure file: {e}", None, None
-    
-    # Extract the specified chain
-    try:
-        chain = structure[0][segment]
-    except KeyError:
-        return "Invalid Chain ID", None, None
-    
-    protein_residues = [res for res in chain if is_aa(res)]
-    sequence = "".join(seq1(res.resname) for res in protein_residues)
-    sequence_id = [res.id[1] for res in protein_residues]
-    
-    input_ids = tokenizer(" ".join(sequence), return_tensors="pt").input_ids.to(device)
-    with torch.no_grad():
-        outputs = model(input_ids).logits.detach().cpu().numpy().squeeze()
-    
-    # Calculate scores and normalize them
-    scores = expit(outputs[:, 1] - outputs[:, 0])
-    
-    normalized_scores = normalize_scores(scores)
-    
-    # Zip residues with scores to track the residue ID and score
-    residue_scores = [(resi, score) for resi, score in zip(sequence_id, normalized_scores)]
-
-    
-    # Define the score brackets
-    score_brackets = {
-        "0.0-0.2": (0.0, 0.2),
-        "0.2-0.4": (0.2, 0.4),
-        "0.4-0.6": (0.4, 0.6),
-        "0.6-0.8": (0.6, 0.8),
-        "0.8-1.0": (0.8, 1.0)
-    }
-    
-    # Initialize a dictionary to store residues by bracket
-    residues_by_bracket = {bracket: [] for bracket in score_brackets}
-    
-    # Categorize residues into brackets
-    for resi, score in residue_scores:
-        for bracket, (lower, upper) in score_brackets.items():
-            if lower <= score < upper:
-                residues_by_bracket[bracket].append(resi)
-                break
-    
-    # Preparing the result string
-    current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-    result_str = f"Prediction for PDB: {pdb_id}, Chain: {segment}\nDate: {current_time}\n\n"
-    result_str += "Residues by Score Brackets:\n\n"
-    
-    # Add residues for each bracket
-    for bracket, residues in residues_by_bracket.items():
-        result_str += f"Bracket {bracket}:\n"
-        result_str += "Columns: Residue Name, Residue Number, One-letter Code, Normalized Score\n"
-        result_str += "\n".join([
-            f"{res.resname} {res.id[1]} {sequence[i]} {normalized_scores[i]:.2f}" 
-            for i, res in enumerate(protein_residues) if res.id[1] in residues
-        ])
-        result_str += "\n\n"
-
-    # Create chain-specific PDB with scores in B-factor
-    scored_pdb = create_chain_specific_pdb(pdb_path, segment, residue_scores, protein_residues)
-
-    # Molecule visualization with updated script with color mapping
-    mol_vis = molecule(pdb_path, residue_scores, segment)#, color_map)
-
-    # Improved PyMOL command suggestions
-    current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-    pymol_commands = f"Prediction for PDB: {pdb_id}, Chain: {segment}\nDate: {current_time}\n\n"
-    
-    pymol_commands += f"""
-    # PyMOL Visualization Commands
-    load {os.path.abspath(pdb_path)}, protein
-    hide everything, all
-    show cartoon, chain {segment}
-    color white, chain {segment}
-    """
-    
-    # Define colors for each score bracket
-    bracket_colors = {
-        "0.0-0.2": "white",
-        "0.2-0.4": "lightorange",
-        "0.4-0.6": "orange",
-        "0.6-0.8": "orangered",
-        "0.8-1.0": "red"
-    }
-    
-    # Add PyMOL commands for each score bracket
-    for bracket, residues in residues_by_bracket.items():
-        if residues:  # Only add commands if there are residues in this bracket
-            color = bracket_colors[bracket]
-            resi_list = '+'.join(map(str, residues))
-            pymol_commands += f"""
-    select bracket_{bracket.replace('.', '').replace('-', '_')}, resi {resi_list} and chain {segment}
-    show sticks, bracket_{bracket.replace('.', '').replace('-', '_')}
-    color {color}, bracket_{bracket.replace('.', '').replace('-', '_')}
-    """
-    # Create prediction and scored PDB files
-    prediction_file = f"{pdb_id}_binding_site_residues.txt"
-    with open(prediction_file, "w") as f:
-        f.write(result_str)
-    
-    return pymol_commands, mol_vis, [prediction_file,scored_pdb]
-
-def molecule(input_pdb, residue_scores=None, segment='A'):
-    # More granular scoring for visualization
-    mol = read_mol(input_pdb)  # Read PDB file content
-
-    # Prepare high-scoring residues script if scores are provided
-    high_score_script = ""
-    if residue_scores is not None:
-        # Filter residues based on their scores
-        class1_score_residues = [resi for resi, score in residue_scores if 0.0 < score <= 0.2]
-        class2_score_residues = [resi for resi, score in residue_scores if 0.2 < score <= 0.4]
-        class3_score_residues = [resi for resi, score in residue_scores if 0.4 < score <= 0.6]
-        class4_score_residues = [resi for resi, score in residue_scores if 0.6 < score <= 0.8]
-        class5_score_residues = [resi for resi, score in residue_scores if 0.8 < score <= 1.0]
-        
-        
-        high_score_script = """
-        // Load the original model and apply white cartoon style
-        let chainModel = viewer.addModel(pdb, "pdb");
-        chainModel.setStyle({}, {});
-        chainModel.setStyle(
-            {"chain": "%s"}, 
-            {"cartoon": {"color": "white"}}
-        );
-
-        // Create a new model for high-scoring residues and apply red sticks style
-        let class1Model = viewer.addModel(pdb, "pdb");
-        class1Model.setStyle({}, {});
-        class1Model.setStyle(
-            {"chain": "%s", "resi": [%s]}, 
-            {"stick": {"color": "0xFFFFFF", "opacity": 0.5}}
-        );
-
-        // Create a new model for high-scoring residues and apply red sticks style
-        let class2Model = viewer.addModel(pdb, "pdb");
-        class2Model.setStyle({}, {});
-        class2Model.setStyle(
-            {"chain": "%s", "resi": [%s]}, 
-            {"stick": {"color": "0xFFD580", "opacity": 0.7}}
-        );
-
-        // Create a new model for high-scoring residues and apply red sticks style
-        let class3Model = viewer.addModel(pdb, "pdb");
-        class3Model.setStyle({}, {});
-        class3Model.setStyle(
-            {"chain": "%s", "resi": [%s]}, 
-            {"stick": {"color": "0xFFA500", "opacity": 1}}
-        );
-
-        // Create a new model for high-scoring residues and apply red sticks style
-        let class4Model = viewer.addModel(pdb, "pdb");
-        class4Model.setStyle({}, {});
-        class4Model.setStyle(
-            {"chain": "%s", "resi": [%s]}, 
-            {"stick": {"color": "0xFF4500", "opacity": 1}}
-        );
-
-        // Create a new model for high-scoring residues and apply red sticks style
-        let class5Model = viewer.addModel(pdb, "pdb");
-        class5Model.setStyle({}, {});
-        class5Model.setStyle(
-            {"chain": "%s", "resi": [%s]}, 
-            {"stick": {"color": "0xFF0000", "alpha": 1}}
-        );
-
-        """ % (
-            segment,
-            segment,
-            ", ".join(str(resi) for resi in class1_score_residues),
-            segment,
-            ", ".join(str(resi) for resi in class2_score_residues),
-            segment,
-            ", ".join(str(resi) for resi in class3_score_residues),
-            segment,
-            ", ".join(str(resi) for resi in class4_score_residues),
-            segment,
-            ", ".join(str(resi) for resi in class5_score_residues)
-        )
-    
-    # Generate the full HTML content
-    html_content = f"""
-    <!DOCTYPE html>
-    <html>
-    <head>    
-        <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
-        <style>
-        .mol-container {{
-            width: 100%;
-            height: 700px;
-            position: relative;
-        }}
-        </style>
-        <script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.6.3/jquery.min.js"></script>
-        <script src="https://3Dmol.csb.pitt.edu/build/3Dmol-min.js"></script>
-    </head>
-    <body>
-        <div id="container" class="mol-container"></div>
-        <script>
-            let pdb = `{mol}`; // Use template literal to properly escape PDB content
-            $(document).ready(function () {{
-                let element = $("#container");
-                let config = {{ backgroundColor: "white" }};
-                let viewer = $3Dmol.createViewer(element, config);
-                
-                {high_score_script}
-                
-                // Add hover functionality
-                viewer.setHoverable(
-                    {{}}, 
-                    true, 
-                    function(atom, viewer, event, container) {{
-                        if (!atom.label) {{
-                            atom.label = viewer.addLabel(
-                                atom.resn + ":" +atom.resi + ":" + atom.atom, 
-                                {{
-                                    position: atom, 
-                                    backgroundColor: 'mintcream', 
-                                    fontColor: 'black',
-                                    fontSize: 18,
-                                    padding: 4
-                                }}
-                            );
-                        }}
-                    }},
-                    function(atom, viewer) {{
-                        if (atom.label) {{
-                            viewer.removeLabel(atom.label);
-                            delete atom.label;
-                        }}
-                    }}
-                );
-                
-                viewer.zoomTo();
-                viewer.render();
-                viewer.zoom(0.8, 2000);
-            }});
-        </script>
-    </body>
-    </html>
-    """
-    
-    # Return the HTML content within an iframe safely encoded for special characters
-    return f'<iframe width="100%" height="700" srcdoc="{html_content.replace(chr(34), "&quot;").replace(chr(39), "&#39;")}"></iframe>'
-
-# Gradio UI
-with gr.Blocks() as demo:
-    gr.Markdown("# Protein Binding Site Prediction")
-    
-    # Mode selection
-    mode = gr.Radio(
-        choices=["PDB ID", "Upload File"],
-        value="PDB ID",
-        label="Input Mode",
-        info="Choose whether to input a PDB ID or upload a PDB/CIF file."
-    )
-
-    # Input components based on mode
-    pdb_input = gr.Textbox(value="4BDU", label="PDB ID", placeholder="Enter PDB ID here...")
-    pdb_file = gr.File(label="Upload PDB/CIF File", visible=False)
-    visualize_btn = gr.Button("Visualize Structure")
-
-    molecule_output2 = Molecule3D(label="Protein Structure", reps=[
-        {
-            "model": 0,
-            "style": "cartoon",
-            "color": "whiteCarbon",
-            "residue_range": "",
-            "around": 0,
-            "byres": False,
-        }
-    ])
-
-    with gr.Row():
-        segment_input = gr.Textbox(value="A", label="Chain ID", placeholder="Enter Chain ID here...")
-        prediction_btn = gr.Button("Predict Binding Site")
-
-    molecule_output = gr.HTML(label="Protein Structure")
-    explanation_vis = gr.Markdown("""
-    Score dependent colorcoding:
-    - 0.0-0.2: white  
-    - 0.2–0.4: light orange  
-    - 0.4–0.6: orange
-    - 0.6–0.8: orangered
-    - 0.8–1.0: red
-    """)
-    predictions_output = gr.Textbox(label="Visualize Prediction with PyMol")
-    gr.Markdown("### Download:\n- List of predicted binding site residues\n- PDB with score in beta factor column")
-    download_output = gr.File(label="Download Files", file_count="multiple")
-    
-    def process_interface(mode, pdb_id, pdb_file, chain_id):
-        if mode == "PDB ID":
-            return process_pdb(pdb_id, chain_id)
-        elif mode == "Upload File":
-            _, ext = os.path.splitext(pdb_file.name)
-            file_path = os.path.join('./', f"{_}{ext}")
-            if ext == '.cif':
-                pdb_path = convert_cif_to_pdb(file_path)
-            else:
-                pdb_path= file_path
-            return process_pdb(pdb_path, chain_id)
-        else:
-            return "Error: Invalid mode selected", None, None
-
-    def fetch_interface(mode, pdb_id, pdb_file):
-        if mode == "PDB ID":
-            return fetch_pdb(pdb_id)
-        elif mode == "Upload File":
-            _, ext = os.path.splitext(pdb_file.name)
-            file_path = os.path.join('./', f"{_}{ext}")
-            #print(ext)
-            if ext == '.cif':
-                pdb_path = convert_cif_to_pdb(file_path)
-            else:
-                pdb_path= file_path
-            #print(pdb_path)
-            return pdb_path
-        else:
-            return "Error: Invalid mode selected"
-
-    def toggle_mode(selected_mode):
-        if selected_mode == "PDB ID":
-            return gr.update(visible=True), gr.update(visible=False)
-        else:
-            return gr.update(visible=False), gr.update(visible=True)
-
-    mode.change(
-        toggle_mode,
-        inputs=[mode],
-        outputs=[pdb_input, pdb_file]
-    )
-
-    prediction_btn.click(
-        process_interface, 
-        inputs=[mode, pdb_input, pdb_file, segment_input], 
-        outputs=[predictions_output, molecule_output, download_output]
-    )
-
-    visualize_btn.click(
-        fetch_interface, 
-        inputs=[mode, pdb_input, pdb_file], 
-        outputs=molecule_output2
-    )
-
-    gr.Markdown("## Examples")
-    gr.Examples(
-        examples=[
-            ["7RPZ", "A"],
-            ["2IWI", "B"],
-            ["2F6V", "A"]
-        ],
-        inputs=[pdb_input, segment_input],
-        outputs=[predictions_output, molecule_output, download_output]
-    )
-
-demo.launch(share=True)

test.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 2,
    "id": "e776d9d6-417e-46d4-8061-846c055e1f8a",
    "metadata": {},
    "outputs": [
@@ -10,8 +10,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "* Running on local URL:  http://127.0.0.1:7873\n",
-      "* Running on public URL: https://120000a6aa9d78e04c.gradio.live\n",
+      "* Running on local URL:  http://127.0.0.1:7860\n",
+      "* Running on public URL: https://17e7c7978ce0b4df12.gradio.live\n",
       "\n",
       "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
      ]
@@ -19,7 +19,7 @@
     {
      "data": {
       "text/html": [
-       "<div><iframe src=\"https://120000a6aa9d78e04c.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+       "<div><iframe src=\"https://17e7c7978ce0b4df12.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -32,7 +32,7 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 29,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -570,36 +570,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 3,
    "id": "d70c40b9-5d5a-4795-b2a2-149c4a57d16e",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/helpers.py:441: UserWarning: Examples will be cached but not all input components have example values. This may result in an exception being thrown by your function. If you do get an error while caching examples, make sure all of your inputs have example values for all of your examples or you provide default values for those particular parameters in your function.\n",
-      "  warnings.warn(\n",
-      "INFO:__main__:Using cached structure: ./7rpz.cif\n",
-      "INFO:__main__:Using cached structure: ./2iwi.cif\n",
-      "INFO:__main__:Using cached structure: ./2f6v.cif\n",
-      "INFO:httpx:HTTP Request: GET http://127.0.0.1:7862/gradio_api/startup-events \"HTTP/1.1 200 OK\"\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "* Running on local URL:  http://127.0.0.1:7862\n",
-      "Caching examples at: '/home/frohlkin/Projects/LargeLanguageModels/Publication/test_webpage/.gradio/cached_examples/148'\n"
+      "* Running on local URL:  http://127.0.0.1:7861\n",
+      "Caching examples at: '/Users/thorben_froehlking/Desktop/PostDoc/Projects/CrypticPockets/test_webpage/.gradio/cached_examples/43'\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "INFO:httpx:HTTP Request: HEAD http://127.0.0.1:7862/ \"HTTP/1.1 200 OK\"\n",
+      "/Users/thorben_froehlking/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/helpers.py:441: UserWarning: Examples will be cached but not all input components have example values. This may result in an exception being thrown by your function. If you do get an error while caching examples, make sure all of your inputs have example values for all of your examples or you provide default values for those particular parameters in your function.\n",
+      "  warnings.warn(\n",
       "INFO:httpx:HTTP Request: GET https://api.gradio.app/pkg-version \"HTTP/1.1 200 OK\"\n",
+      "INFO:__main__:Successfully downloaded: https://files.rcsb.org/download/7RPZ.cif\n",
+      "INFO:__main__:Successfully downloaded: https://files.rcsb.org/download/2IWI.cif\n",
+      "INFO:__main__:Successfully downloaded: https://files.rcsb.org/download/2F6V.cif\n",
+      "INFO:httpx:HTTP Request: GET http://127.0.0.1:7861/gradio_api/startup-events \"HTTP/1.1 200 OK\"\n",
+      "INFO:httpx:HTTP Request: HEAD http://127.0.0.1:7861/ \"HTTP/1.1 200 OK\"\n",
       "INFO:httpx:HTTP Request: GET https://api.gradio.app/v3/tunnel-request \"HTTP/1.1 200 OK\"\n"
      ]
     },
@@ -607,7 +601,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "* Running on public URL: https://de785d7cce806497e9.gradio.live\n",
+      "* Running on public URL: https://c7596f9c4fd96dd249.gradio.live\n",
       "\n",
       "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
      ]
@@ -616,13 +610,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "INFO:httpx:HTTP Request: HEAD https://de785d7cce806497e9.gradio.live \"HTTP/1.1 200 OK\"\n"
+      "INFO:httpx:HTTP Request: HEAD https://c7596f9c4fd96dd249.gradio.live \"HTTP/1.1 200 OK\"\n"
      ]
     },
     {
      "data": {
       "text/html": [
-       "<div><iframe src=\"https://de785d7cce806497e9.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+       "<div><iframe src=\"https://c7596f9c4fd96dd249.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -635,135 +629,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Traceback (most recent call last):\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/routes.py\", line 990, in predict\n",
-      "    output = await route_utils.call_process_api(\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/route_utils.py\", line 322, in call_process_api\n",
-      "    output = await app.get_blocks().process_api(\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/blocks.py\", line 2047, in process_api\n",
-      "    result = await self.call_function(\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/blocks.py\", line 1594, in call_function\n",
-      "    prediction = await anyio.to_thread.run_sync(  # type: ignore\n",
-      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/anyio/to_thread.py\", line 56, in run_sync\n",
-      "    return await get_async_backend().run_sync_in_worker_thread(\n",
-      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/anyio/_backends/_asyncio.py\", line 2405, in run_sync_in_worker_thread\n",
-      "    return await future\n",
-      "           ^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/anyio/_backends/_asyncio.py\", line 914, in run\n",
-      "    result = context.run(func, *args)\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/utils.py\", line 869, in wrapper\n",
-      "    response = f(*args, **kwargs)\n",
-      "               ^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/helpers.py\", line 355, in load_example_with_output\n",
-      "    ) + self.load_from_cache(example_id)\n",
-      "        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/helpers.py\", line 579, in load_from_cache\n",
-      "    output.append(component.read_from_flag(value_to_use))\n",
-      "                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/components/base.py\", line 366, in read_from_flag\n",
-      "    return self.data_model.from_json(json.loads(payload))\n",
-      "                                     ^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/json/__init__.py\", line 346, in loads\n",
-      "    return _default_decoder.decode(s)\n",
-      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/json/decoder.py\", line 337, in decode\n",
-      "    obj, end = self.raw_decode(s, idx=_w(s, 0).end())\n",
-      "               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/json/decoder.py\", line 355, in raw_decode\n",
-      "    raise JSONDecodeError(\"Expecting value\", s, err.value) from None\n",
-      "json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)\n",
-      "Traceback (most recent call last):\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/routes.py\", line 990, in predict\n",
-      "    output = await route_utils.call_process_api(\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/route_utils.py\", line 322, in call_process_api\n",
-      "    output = await app.get_blocks().process_api(\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/blocks.py\", line 2047, in process_api\n",
-      "    result = await self.call_function(\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/blocks.py\", line 1594, in call_function\n",
-      "    prediction = await anyio.to_thread.run_sync(  # type: ignore\n",
-      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/anyio/to_thread.py\", line 56, in run_sync\n",
-      "    return await get_async_backend().run_sync_in_worker_thread(\n",
-      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/anyio/_backends/_asyncio.py\", line 2405, in run_sync_in_worker_thread\n",
-      "    return await future\n",
-      "           ^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/anyio/_backends/_asyncio.py\", line 914, in run\n",
-      "    result = context.run(func, *args)\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/utils.py\", line 869, in wrapper\n",
-      "    response = f(*args, **kwargs)\n",
-      "               ^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/helpers.py\", line 355, in load_example_with_output\n",
-      "    ) + self.load_from_cache(example_id)\n",
-      "        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/helpers.py\", line 579, in load_from_cache\n",
-      "    output.append(component.read_from_flag(value_to_use))\n",
-      "                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/components/base.py\", line 366, in read_from_flag\n",
-      "    return self.data_model.from_json(json.loads(payload))\n",
-      "                                     ^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/json/__init__.py\", line 346, in loads\n",
-      "    return _default_decoder.decode(s)\n",
-      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/json/decoder.py\", line 337, in decode\n",
-      "    obj, end = self.raw_decode(s, idx=_w(s, 0).end())\n",
-      "               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/json/decoder.py\", line 355, in raw_decode\n",
-      "    raise JSONDecodeError(\"Expecting value\", s, err.value) from None\n",
-      "json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)\n",
-      "Traceback (most recent call last):\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/routes.py\", line 990, in predict\n",
-      "    output = await route_utils.call_process_api(\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/route_utils.py\", line 322, in call_process_api\n",
-      "    output = await app.get_blocks().process_api(\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/blocks.py\", line 2047, in process_api\n",
-      "    result = await self.call_function(\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/blocks.py\", line 1594, in call_function\n",
-      "    prediction = await anyio.to_thread.run_sync(  # type: ignore\n",
-      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/anyio/to_thread.py\", line 56, in run_sync\n",
-      "    return await get_async_backend().run_sync_in_worker_thread(\n",
-      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/anyio/_backends/_asyncio.py\", line 2405, in run_sync_in_worker_thread\n",
-      "    return await future\n",
-      "           ^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/anyio/_backends/_asyncio.py\", line 914, in run\n",
-      "    result = context.run(func, *args)\n",
-      "             ^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/utils.py\", line 869, in wrapper\n",
-      "    response = f(*args, **kwargs)\n",
-      "               ^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/helpers.py\", line 355, in load_example_with_output\n",
-      "    ) + self.load_from_cache(example_id)\n",
-      "        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/helpers.py\", line 579, in load_from_cache\n",
-      "    output.append(component.read_from_flag(value_to_use))\n",
-      "                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/site-packages/gradio/components/base.py\", line 366, in read_from_flag\n",
-      "    return self.data_model.from_json(json.loads(payload))\n",
-      "                                     ^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/json/__init__.py\", line 346, in loads\n",
-      "    return _default_decoder.decode(s)\n",
-      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/json/decoder.py\", line 337, in decode\n",
-      "    obj, end = self.raw_decode(s, idx=_w(s, 0).end())\n",
-      "               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-      "  File \"/home/frohlkin/anaconda3/envs/LLM/lib/python3.12/json/decoder.py\", line 355, in raw_decode\n",
-      "    raise JSONDecodeError(\"Expecting value\", s, err.value) from None\n",
-      "json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)\n"
+      "INFO:__main__:Using cached structure: ./2f6v.cif\n"
      ]
     }
    ],
@@ -1491,9 +1357,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python (LLM)",
+   "display_name": "Python [conda env:LLM]",
    "language": "python",
-   "name": "llm"
+   "name": "conda-env-LLM-py"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1505,7 +1371,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.2"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,