| name | bio-substructure-search |
| description | Searches molecular libraries for substructure matches using SMARTS patterns with RDKit. Filters compounds by pharmacophore features, functional groups, or scaffold matches with atom mapping. Use when finding compounds containing specific chemical moieties or filtering libraries by structural features. |
| tool_type | python |
| primary_tool | RDKit |
Substructure Search
Find molecules containing specific structural patterns using SMARTS.
Basic Substructure Search
from rdkit import Chem
mol = Chem.MolFromSmiles('c1ccc(O)cc1CCO')
pattern = Chem.MolFromSmarts('[OH]')
has_hydroxyl = mol.HasSubstructMatch(pattern)
print(f'Contains hydroxyl: {has_hydroxyl}')
matches = mol.GetSubstructMatches(pattern)
print(f'Hydroxyl positions: {matches}')
Common SMARTS Patterns
| Pattern | SMARTS | Description |
|---|
| Hydroxyl | [OH] | Alcohol/phenol |
| Primary amine | [NH2] | Primary amine |
| Secondary amine | [NH1] | Secondary amine |
| Carboxylic acid | [CX3](=O)[OX2H1] | COOH |
| Amide | [CX3](=O)[NX3] | C(=O)N |
| Benzene | c1ccccc1 | Phenyl ring |
| Any aromatic | [a] | Any aromatic atom |
| Halogen | [F,Cl,Br,I] | Any halogen |
Library Filtering
from rdkit import Chem
def filter_by_substructure(molecules, smarts, exclude=False):
'''
Filter molecules by substructure presence/absence.
Args:
molecules: List of RDKit mol objects
smarts: SMARTS pattern string
exclude: If True, return molecules WITHOUT the pattern
'''
pattern = Chem.MolFromSmarts(smarts)
if pattern is None:
raise ValueError(f'Invalid SMARTS: {smarts}')
filtered = []
for mol in molecules:
if mol is None:
continue
has_match = mol.HasSubstructMatch(pattern)
if exclude:
if not has_match:
filtered.append(mol)
else:
if has_match:
filtered.append(mol)
return filtered
amines = filter_by_substructure(library, '[NX3;H2,H1,H0]')
clean = filter_by_substructure(library, '[N+]([O-])=O', exclude=True)
Multiple Pattern Filtering
def filter_multiple_patterns(molecules, include_patterns=None, exclude_patterns=None):
'''
Filter by multiple inclusion and exclusion patterns.
'''
result = list(molecules)
if include_patterns:
for smarts in include_patterns:
pattern = Chem.MolFromSmarts(smarts)
result = [m for m in result if m and m.HasSubstructMatch(pattern)]
if exclude_patterns:
for smarts in exclude_patterns:
pattern = Chem.MolFromSmarts(smarts)
result = [m for m in result if m and not m.HasSubstructMatch(pattern)]
return result
amino_acids = filter_multiple_patterns(
library,
include_patterns=['[NX3;H2]', '[CX3](=O)[OX2H1]']
)
Atom Mapping
from rdkit import Chem
def get_substructure_atoms(mol, smarts):
'''
Get all atoms matching a pattern with their indices.
'''
pattern = Chem.MolFromSmarts(smarts)
matches = mol.GetSubstructMatches(pattern)
results = []
for match in matches:
atoms = [mol.GetAtomWithIdx(i) for i in match]
results.append({
'indices': match,
'symbols': [a.GetSymbol() for a in atoms]
})
return results
mol = Chem.MolFromSmiles('c1ccc2c(c1)cccc2')
rings = get_substructure_atoms(mol, 'c1ccccc1')
print(f'Found {len(rings)} aromatic 6-membered rings')
Recursive SMARTS
pattern = '[$(c1ccccc1C(=O))]'
ortho_pattern = '[$(c1ccc([*])cc1[*])]'
ewg_aromatic = '[$(c[$(C(=O)),$(C#N),$(N(=O)=O)])]'
mol = Chem.MolFromSmiles('c1ccc(C(=O)O)cc1')
pattern = Chem.MolFromSmarts('[$(c1ccccc1C(=O))]')
print(mol.HasSubstructMatch(pattern))
Visualization with Highlighting
from rdkit.Chem.Draw import rdMolDraw2D
def draw_with_highlights(mol, smarts, filename):
'''Draw molecule with substructure highlighted.'''
pattern = Chem.MolFromSmarts(smarts)
match = mol.GetSubstructMatch(pattern)
if not match:
print('No match found')
return
drawer = rdMolDraw2D.MolDraw2DCairo(400, 300)
drawer.DrawMolecule(mol, highlightAtoms=match)
drawer.FinishDrawing()
with open(filename, 'wb') as f:
f.write(drawer.GetDrawingText())
draw_with_highlights(mol, '[CX3](=O)[OX2H1]', 'highlighted.png')
Related Skills
- molecular-io - Load molecules for searching
- similarity-searching - Fingerprint-based searching
- admet-prediction - Filter before ADMET analysis