Proper RMSD calculation between molecules using the Kuhn-Munkres Hungarian algorithm.
Project description
RMSD
Determining the Root Mean Square Deviation (RMSD) between the Maximum Common Substructures (MCS) of two molecules.
The Kuhn-Munkres Hungarian algorithm allows for a fast match of atoms based on:
- atomic symbol
- Sybyl atom types
- pharmacophoric types (i.e. H-bond donors and acceptors or charges)
Installation
pip install munkres-rmsd
Example
from munkres_rmsd import CalcLigRMSD, AtomType
from munkres_rmsd.RMSD import get_example_molecules
# First, load 3D poses of molecules
mol1, mol2 = get_example_molecules()
# Then compute the RMSD of the best atomic match
rmsd = CalcLigRMSD(mol1, mol2)
print(rmsd) # 10.76150...
Let's use Sybyl atom types to match atoms between the two molecules instead of the default, using atomic elements.
# Then compute the RMSD of the best atomic match
rmsd = CalcLigRMSD(mol1, mol2, AtomType.Sybyl)
print(rmsd) # 11.59752...
Should you prefer pharmacophore types (i.e. H-bond donors & acceptors, charges and others):
# Then compute the RMSD of the best atomic match
rmsd = CalcLigRMSD(mol1, mol2, AtomType.Pharmacophore)
print(rmsd) # 9.49120...
Finally to allow matching any atom whatever its type:
# Then compute the RMSD of the best atomic match
rmsd = CalcLigRMSD(mol1, mol2, AtomType.Skeleton)
print(rmsd) # 8.96288...
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