OpenClaw-Medical-Skills bio-molecular-io
Reads, writes, and converts molecular file formats (SMILES, SDF, MOL2, PDB) using RDKit and Open Babel. Handles structure parsing, canonicalization, and full standardization pipeline including sanitization, normalization, and tautomer canonicalization. Use when loading chemical libraries, converting formats, or preparing molecules for analysis.
git clone https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/bio-molecular-io" ~/.claude/skills/freedomintelligence-openclaw-medical-skills-bio-molecular-io && rm -rf "$T"
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/bio-molecular-io" ~/.openclaw/skills/freedomintelligence-openclaw-medical-skills-bio-molecular-io && rm -rf "$T"
skills/bio-molecular-io/SKILL.mdVersion Compatibility
Reference examples tested with: RDKit 2024.03+
Before using code patterns, verify installed versions match. If versions differ:
- Python:
thenpip show <package>
to check signatureshelp(module.function)
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Molecular I/O
"Load my chemical library into Python" → Parse molecular file formats (SMILES, SDF, MOL2, PDB) into RDKit molecule objects for programmatic access, standardization, and format conversion.
- Python:
,Chem.MolFromSmiles()
(RDKit)Chem.SDMolSupplier()
Read, write, and convert molecular file formats with structure standardization.
Supported Formats
| Format | Extension | Use Case |
|---|---|---|
| SMILES | .smi | Text representation, databases |
| SDF/MOL | .sdf, .mol | 3D structures, compound libraries |
| MOL2 | .mol2 | Docking, force field atoms |
| PDB | .pdb | Protein-ligand complexes |
Reading Molecules
Goal: Load molecules from SMILES strings, SDF files, or SMILES files into RDKit molecule objects.
Approach: Use Chem.MolFromSmiles for individual SMILES, SDMolSupplier for multi-molecule SDF files, and file iteration for SMILES files, filtering out parse failures.
from rdkit import Chem from rdkit.Chem import AllChem # From SMILES mol = Chem.MolFromSmiles('CCO') # From SDF file (single molecule) mol = Chem.MolFromMolFile('molecule.mol') # From SDF file (multiple molecules) supplier = Chem.SDMolSupplier('library.sdf') molecules = [mol for mol in supplier if mol is not None] print(f'Loaded {len(molecules)} molecules') # From SMILES file with open('compounds.smi') as f: molecules = [] for line in f: parts = line.strip().split() if parts: mol = Chem.MolFromSmiles(parts[0]) if mol: mol.SetProp('_Name', parts[1] if len(parts) > 1 else '') molecules.append(mol)
Writing Molecules
from rdkit import Chem # To SMILES smiles = Chem.MolToSmiles(mol) # Canonical SMILES smiles_iso = Chem.MolToSmiles(mol, isomericSmiles=True) # With stereochemistry # To SDF file writer = Chem.SDWriter('output.sdf') for mol in molecules: writer.write(mol) writer.close() # To MOL block (string) mol_block = Chem.MolToMolBlock(mol)
Structure Standardization
Goal: Normalize molecular representations to a canonical form for consistent comparison and analysis.
Approach: Apply a multi-step pipeline: sanitize valences, normalize functional groups, neutralize charges, canonicalize tautomers, and strip salts using rdMolStandardize.
Use rdMolStandardize module (Python MolStandardize was removed Q1 2024).
from rdkit import Chem from rdkit.Chem.MolStandardize import rdMolStandardize def standardize_molecule(mol): ''' Full standardization pipeline. Order: Sanitize -> Normalize -> Neutralize -> Canonicalize tautomer -> Strip salts ''' if mol is None: return None # Sanitize (assign valences, kekulize) try: Chem.SanitizeMol(mol) except Exception: return None # Normalize (standardize functional groups) normalizer = rdMolStandardize.Normalizer() mol = normalizer.normalize(mol) # Neutralize charges where possible uncharger = rdMolStandardize.Uncharger() mol = uncharger.uncharge(mol) # Canonicalize tautomers enumerator = rdMolStandardize.TautomerEnumerator() mol = enumerator.Canonicalize(mol) # Remove salts/fragments (keep largest) remover = rdMolStandardize.FragmentRemover() mol = remover.remove(mol) return mol # Standardize a library standardized = [standardize_molecule(m) for m in molecules] standardized = [m for m in standardized if m is not None]
Open Babel Conversion
For format conversions not supported by RDKit.
# Open Babel 3.x import (not 'import pybel') from openbabel import pybel # Read MOL2 (better supported in Open Babel) mols = list(pybel.readfile('mol2', 'ligands.mol2')) # Convert to SDF output = pybel.Outputfile('sdf', 'output.sdf', overwrite=True) for mol in mols: output.write(mol) output.close() # Format conversion for mol in pybel.readfile('pdb', 'complex.pdb'): mol.write('mol2', 'ligand.mol2', overwrite=True)
Molecular Drawing
Use rdMolDraw2D (legacy Draw.MolToImage deprecated).
from rdkit import Chem from rdkit.Chem.Draw import rdMolDraw2D def draw_molecule(mol, filename, size=(400, 300)): '''Draw molecule to PNG file.''' drawer = rdMolDraw2D.MolDraw2DCairo(size[0], size[1]) drawer.DrawMolecule(mol) drawer.FinishDrawing() with open(filename, 'wb') as f: f.write(drawer.GetDrawingText()) # Draw with highlighting def draw_with_substructure(mol, pattern, filename): '''Highlight substructure match.''' match = mol.GetSubstructMatch(Chem.MolFromSmarts(pattern)) drawer = rdMolDraw2D.MolDraw2DCairo(400, 300) drawer.DrawMolecule(mol, highlightAtoms=match) drawer.FinishDrawing() with open(filename, 'wb') as f: f.write(drawer.GetDrawingText())
Related Skills
- molecular-descriptors - Calculate properties after loading
- similarity-searching - Compare loaded molecules
- virtual-screening - Prepare ligands for docking