protein-ligand-binding-analysis-plip

name	protein-ligand-binding-analysis-plip
description	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
category	binding-affinity
tags	["protein-ligand","interaction-analysis","plip","visualization","docking"]

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.