Fragment and Scaffold

In [1]:

%load_ext autoreload
%autoreload 2

%load_ext autoreload %autoreload 2

In [2]:

import datamol as dm
dm.disable_rdkit_log()

import datamol as dm dm.disable_rdkit_log()

Fragmentation¶

The fragmentation methods implemented in datamol will return the fragment set coverage of a molecule, as opposed to a break down of the molecules into non-overlapping blocks.

In the following, let's fragment a molecule using multiple methods.

In [3]:

smiles = "CCCOCc1cc(c2ncccc2)ccc1"
mol = dm.to_mol(smiles)
mol

smiles = "CCCOCc1cc(c2ncccc2)ccc1" mol = dm.to_mol(smiles) mol

Out[3]:

BRICS¶

In [4]:

frags = dm.fragment.brics(mol)
dm.viz.to_image(frags, n_cols=6)

frags = dm.fragment.brics(mol) dm.viz.to_image(frags, n_cols=6)

Out[4]:

FraggleSim¶

In [5]:

frags = dm.fragment.frag(mol)
dm.viz.to_image(frags, n_cols=6)

frags = dm.fragment.frag(mol) dm.viz.to_image(frags, n_cols=6)

Out[5]:

Recap¶

In [6]:

frags = dm.fragment.recap(mol)
dm.viz.to_image(frags, n_cols=6)

frags = dm.fragment.recap(mol) dm.viz.to_image(frags, n_cols=6)

Out[6]:

Any break¶

This method uses BRICS first and fallback to generating all possible fragmentation if it doesn't work.

In [7]:

frags = dm.fragment.anybreak(mol)
dm.viz.to_image(frags, n_cols=6)

frags = dm.fragment.anybreak(mol) dm.viz.to_image(frags, n_cols=6)

Out[7]:

Scaffold¶

Get the scaffolds and attachment points from a list of molecules to allow creating molecular series.

In [8]:

# Get some mols
data = dm.data.freesolv()
smiles = data["smiles"].iloc[:].tolist()
mols = [dm.to_mol(s) for s in smiles]

scaffolds, scf2infos, scf2groups = dm.scaffold.fuzzy_scaffolding(mols)
list(scaffolds)[:4]

# Get some mols data = dm.data.freesolv() smiles = data["smiles"].iloc[:].tolist() mols = [dm.to_mol(s) for s in smiles] scaffolds, scf2infos, scf2groups = dm.scaffold.fuzzy_scaffolding(mols) list(scaffolds)[:4]

Out[8]:

['c1cc2c([*:4])c([*:3])c([*:2])cc2cc1[*:5]',
 'C(=C1c2ccccc2CCc2ccccc21)[*:1]',
 'c1c([*:7])c2c(c([*:8])c1[*:9])Cc1c(c([*:1])c([*:2])c([*:3])c1[*:4])C2',
 'CCc1cc([*:5])cc2cc([*:2])c([*:3])c([*:4])c12']

In [9]:

sfs = [dm.to_mol(s) for s in list(scaffolds)]
dm.viz.to_image(sfs, n_cols=6)

sfs = [dm.to_mol(s) for s in list(scaffolds)] dm.viz.to_image(sfs, n_cols=6)

Out[9]: