PDB-SDF Docking Viewer Setup

Requirements

Create a requirements.txt file:

streamlit>=1.28.0
pandas>=1.5.0
rdkit-pypi>=2022.9.0
py3Dmol>=2.0.0
numpy>=1.24.0
pathlib

Installation

1. Install dependencies:

pip install -r requirements.txt

2. Install AutoDock Vina (for rescoring functionality):

# Option 1: Using conda
conda install -c conda-forge autodock-vina

# Option 2: Download from official site
# https://vina.scripps.edu/downloads/

3. Set up OpenDock environment:

# Create the opendock environment
conda create -n opendock python=3.9
conda activate opendock

# Install OpenDock and its dependencies
# (Follow OpenDock specific installation instructions)
pip install opendock  # or your specific installation method

Usage

1. Run the app:

streamlit run pdb_sdf_docking_viewer.py

Customization

Score Extraction

To add support for additional score property names, modify the score_keys list in parse_sdf_with_scores:

score_keys = ['docking_score', 'score', 'vina_score', 'affinity', 'binding_energy', 'your_custom_score']

Advanced Features

Batch VINA Rescoring

To rescore all ligands at once, you can modify the app to include:

if st.button("🎯 Rescore All Ligands"):
    progress_bar = st.progress(0)
    for i, ligand in enumerate(st.session_state.ligands):
        vina_score = run_vina_rescoring(
            st.session_state.protein_content, 
            ligand['mol_block']
        )
        if vina_score:
            ligand['vina_score'] = vina_score
        progress_bar.progress((i + 1) / len(st.session_state.ligands))

Export Results

Add functionality to export rescored ligands:

if st.button("💾 Export Results"):
    results_df = pd.DataFrame([
        {
            'name': lig['name'],
            'original_score': lig['score'],
            'vina_score': lig.get('vina_score', 'N/A'),
            'mw': lig['mw'],
            'logp': lig['logp']
        }
        for lig in st.session_state.ligands
    ])
    st.download_button(
        "Download CSV",
        results_df.to_csv(index=False),
        "docking_results.csv",
        "text/csv"
    )