Meeko reads an RDKit molecule object and writes a PDBQT string (or file) for AutoDock-Vina and AutoDock-GPU. Additionally, it has tools for post-processing of docking results which are not yet fully developed. Meeko supports the following features:
- Docking with explicit water molecules attached to the ligand (paper)
- Sampling of macrocyclic conformations during docking (paper)
- Creation of RDKit molecules with docked coordinates from PDBQT or DLG files without loss of bond orders.
Meeko is developed by the Forli lab at the Center for Computational Structural Biology (CCSB) at Scripps Research.
The --pH
option was removed since v0.3.0
. See issue forlilab#11 for more info.
- Python (>=3.5)
- Numpy
- Scipy
- RDKit
Conda or Miniconda can install the dependencies:
conda install -c conda-forge numpy scipy rdkit
$ pip install meeko
If using conda, pip
installs the package in the active environment.
$ git clone https://github.com/forlilab/Meeko
$ cd Meeko
$ pip install .
Optionally include --editable
. Changes in the original package location
take effect immediately without the need to run pip install .
again.
$ pip install --editable .
Meeko does not calculate 3D coordinates or assign protonation states. Input molecules must have explicit hydrogens.
mk_prepare_ligand.py -i molecule.sdf -o molecule.pdbqt
mk_prepare_ligand.py -i multi_mol.sdf --multimol_outdir folder_for_pdbqt_files
mk_copy_coords.py vina_results.pdbqt -o vina_results.sdf
mk_copy_coords.py adgpu_results.dlg -o adgpu_results.sdf
from meeko import MoleculePreparation
from rdkit import Chem
input_molecule_file = 'example/BACE_macrocycle/BACE_4.mol2'
mol = Chem.MolFromMol2File(input_molecule_file)
preparator = MoleculePreparation(hydrate=True) # macrocycles flexible by default since v0.3.0
preparator.prepare(mol)
preparator.show_setup()
output_pdbqt_file = "test_macrocycle_hydrate.pdbqt"
preparator.write_pdbqt_file(output_pdbqt_file)
Alternatively, the preparator can be initialized from a dictionary,
which is useful for saving and loading configuration files with json.
The command line tool mk_prepare_ligand.py
can read the json files.
import json
from meeko import MoleculePreparation
mk_config = {"hydrate": True}
print(json.dumps(mk_config), file=open('mk_config.json', 'w'))
with open('mk_config.json') as f:
mk_config = json.load(f)
preparator = MoleculePreparation.from_config(mk_config)
Assuming that 'docked.dlg' was written by AutoDock-GPU and that Meeko prepared the input ligands.
from meeko import PDBQTMolecule
with open("docked.dlg") as f:
dlg_string = f.read()
pdbqt_mol = PDBQTMolecule(dlg_string, is_dlg=True, skip_typing=True)
# alternatively, read the .dlg file directly
pdbqt_mol = PDBQTMolecule.from_file("docked.dlg", is_dlg=True, skip_typing=True)
for pose in pdbqt_mol:
rdkit_mol = pose.export_rdkit_mol()
For Vina's output PDBQT files, omit is_dlg=True
.
pdbqt_mol = PDBQTMolecule.from_file("docking_results_from_vina.pdbqt", skip_typing=True)