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Protein Ligand Binding Analysis Plip by pharmolix

Name: Protein Ligand Binding Analysis Plip
Author: pharmolix

Protein Ligand Binding Analysis Plip

Analyze protein-ligand interactions in PDB structures using PLIP (Protein-Ligand Interaction Profiler). Use this skill when: (1) Analyzing binding interactions from a PDB structure file, (2) Identifying hydrogen bonds, hydrophobic contacts, π-stacking, salt bridges, and water bridges, (3) Generating 3D visualizations of protein-ligand complexes, (4) Creating interaction summary reports for drug discovery.

pharmolix Updated Sep 17, 2026

File contents

Protein-Ligand Binding Analysis with PLIP

Analyze protein-ligand interactions in PDB structures, generate comprehensive interaction reports, and create 3D visualizations.

When to Use

Analyzing binding modes from crystal structures or docking results
Identifying key interactions driving binding affinity
Comparing ligand binding patterns across multiple structures
Generating publication-ready interaction visualizations

Workflow

Step 1: Load PDB and Identify Ligands

from plip.structure.preparation import PDBComplex

complex = PDBComplex()
complex.load_pdb(pdb_file)

# Filter ligands by molecular weight (exclude ions/cofactors, MW > 150 Da)
ligands = []
for lig in complex.ligands:
    if lig.mol.molwt > 150:  # OpenBabel molecule object
        ligands.append(lig)
        complex.characterize_complex(lig)

Step 2: Analyze Interactions

from plip.exchange.report import BindingSiteReport

complex.analyze()

for key, interactions in complex.interaction_sets.items():
    report = BindingSiteReport(interactions)
    report_lines = report.generate_txt()
    # Parse interaction data from report_lines

Step 3: Generate Visualizations

from plip.basic.remote import VisualizerData
from plip.visualization.visualize import visualize_in_pymol
from plip.basic import config

config.PICS = True
config.OUTPATH = output_dir
config.BACKGROUND = "white"
config.CARTOON = True

for key in complex.interaction_sets:
    data = VisualizerData(complex, key)
    visualize_in_pymol(data)

Expected Outputs

Output	Description
Interaction Report	Markdown summary of all interaction types per ligand
Visualization Images	PNG files showing 3D interaction diagrams
Summary Statistics	Counts of H-bonds, hydrophobic, π-stacking, etc.

Interaction Types Reported

Type	Description
Hydrogen bonds	H-bonds with ligand/protein as donor
Hydrophobic contacts	Non-polar interactions
Water bridges	Water-mediated interactions
π-stacking	Aromatic ring interactions
Salt bridges	Ionic interactions
Halogen bonds	Halogen-mediated contacts
Metal complexes	Metal coordination

Score Interpretation

More H-bonds: Generally indicates stronger, more specific binding
Hydrophobic contacts: Contribute to binding entropy
Water bridges: Can enhance or reduce binding affinity
π-stacking: Important for aromatic ligand recognition

Error Handling

Error	Solution
No ligands found	Check PDB file format; ligand may need HETATM records
PLIP characterization fails	Ligand may be malformed; try alternative PDB source
PyMOL visualization fails	Ensure PyMOL is installed and in PATH
Low MW ligands filtered	Adjust MW threshold if small molecules are targets

Dependencies

pip install plip pymol-open-source

Example Usage

# Analyze EGFR-erlotinib complex (1M17)
python examples/basic_example.py --pdb tmp/pdb_1m17.pdb --output ./results/

See examples/basic_example.py for complete implementation and references/advanced.md for batch processing workflows.

---name: protein-ligand-binding-analysis-plipdescription: Analyze protein-ligand interactions in PDB structures using PLIP (Protein-Ligand Interaction Profiler). Use this skill when: (1) Analyzing binding interactions from a PDB structure file, (2) Identifying hydrogen bonds, hydrophobic contacts, π-stacking, salt bridges, and water bridges, (3) Generating 3D visualizations of protein-ligand complexes, (4) Creating interaction summary reports for drug discovery.license: MIT---# Protein-Ligand Binding Analysis with PLIPAnalyze protein-ligand interactions in PDB structures, generate comprehensive interaction reports, and create 3D visualizations.## When to Use- Analyzing binding modes from crystal structures or docking results- Identifying key interactions driving binding affinity- Comparing ligand binding patterns across multiple structures- Generating publication-ready interaction visualizations## Workflow### Step 1: Load PDB and Identify Ligands```pythonfrom plip.structure.preparation import PDBComplexcomplex = PDBComplex()complex.load_pdb(pdb_file)# Filter ligands by molecular weight (exclude ions/cofactors, MW > 150 Da)ligands = []for lig in complex.ligands: if lig.mol.molwt > 150: # OpenBabel molecule object ligands.append(lig) complex.characterize_complex(lig)```### Step 2: Analyze Interactions```pythonfrom plip.exchange.report import BindingSiteReportcomplex.analyze()for key, interactions in complex.interaction_sets.items(): report = BindingSiteReport(interactions) report_lines = report.generate_txt() # Parse interaction data from report_lines```### Step 3: Generate Visualizations```pythonfrom plip.basic.remote import VisualizerDatafrom plip.visualization.visualize import visualize_in_pymolfrom plip.basic import configconfig.PICS = Trueconfig.OUTPATH = output_dirconfig.BACKGROUND = "white"config.CARTOON = Truefor key in complex.interaction_sets: data = VisualizerData(complex, key) visualize_in_pymol(data)```## Expected Outputs| Output | Description ||--------|-------------|| Interaction Report | Markdown summary of all interaction types per ligand || Visualization Images | PNG files showing 3D interaction diagrams || Summary Statistics | Counts of H-bonds, hydrophobic, π-stacking, etc. |### Interaction Types Reported| Type | Description ||------|-------------|| Hydrogen bonds | H-bonds with ligand/protein as donor || Hydrophobic contacts | Non-polar interactions || Water bridges | Water-mediated interactions || π-stacking | Aromatic ring interactions || Salt bridges | Ionic interactions || Halogen bonds | Halogen-mediated contacts || Metal complexes | Metal coordination |## Score Interpretation- **More H-bonds**: Generally indicates stronger, more specific binding- **Hydrophobic contacts**: Contribute to binding entropy- **Water bridges**: Can enhance or reduce binding affinity- **π-stacking**: Important for aromatic ligand recognition## Error Handling| Error | Solution ||-------|----------|| No ligands found | Check PDB file format; ligand may need HETATM records || PLIP characterization fails | Ligand may be malformed; try alternative PDB source || PyMOL visualization fails | Ensure PyMOL is installed and in PATH || Low MW ligands filtered | Adjust MW threshold if small molecules are targets |## Dependencies```bashpip install plip pymol-open-source```## Example Usage```python# Analyze EGFR-erlotinib complex (1M17)python examples/basic_example.py --pdb tmp/pdb_1m17.pdb --output ./results/```See `examples/basic_example.py` for complete implementation and `references/advanced.md` for batch processing workflows.

Frequently asked questions