Examples - Python

TIES also offers a python API. Here is a minimal example:

from ties import Pair

# load the two ligands and use the default configuration
pair = Pair('l02.mol2', 'l03.mol2')
# superimpose the ligands passed above
hybrid = pair.superimpose()

# save the results
hybrid.write_metadata('meta_l02_l03.json')
hybrid.write_pdb('l02_l03_morph.pdb')
hybrid.write_mol2('l02_l03_morph.mol2')

This minimal example can be extended with the protein to generate the input for the TIES_MD package for the simulations in either NAMD or OpenMM.

Note that in this example we do not set any explicit settings. For that we need to employ the Config class which we can then pass to the Pair.

Info

Config contains the settings for all classes in the TIES package, and therefore can be used to define a protocol.

Whereas all settings can be done in :class:Config, for clarity some can be passed separately here to the :class:Pair. This way, it overwrites the settings in the config object:

from ties import Pair
from ties import Config
from ties import Protein


config = Config()
# configure the two settings
config.workdir = 'ties20'
config.md_engine = 'openmm'
# set ligand_net_charge as a parameter,
# which is equivalent to using config.ligand_net_charge
pair = Pair('l02.mol2', 'l03.mol2', ligand_net_charge=-1, config=config)
# rename atoms to help with any issues
pair.make_atom_names_unique()

hybrid = pair.superimpose()

# save meta data to files
hybrid.write_metadata()
hybrid.write_pdb()
hybrid.write_mol2()

# add the protein for the full RBFE protocol
config.protein = 'protein.pdb'
config.protein_ff = 'leaprc.protein.ff14SB'
protein = Protein(config.protein, config)
hybrid.prepare_inputs(protein=protein)

Below we show the variation in which we are using :class:Config to pass the net charge of the molecule.

from ties import Pair
from ties import Config

# explicitly create config (which will be used by all classes underneath)
config = Config()
config.ligand_net_charge = -1

pair = Pair('l02.mol2', 'l03.mol2', config=config)
pair.make_atom_names_unique()

# overwrite the previous config settings with relevant parameters
hybrid = pair.superimpose(use_element_in_superimposition=True, redistribute_q_over_unmatched=True)

# save meta data to specific locations
hybrid.write_metadata('result.json')
hybrid.write_pdb('result.pdb')
hybrid.write_mol2('result.mol2')

hybrid.prepare_inputs()

Note that there is also the :class:Ligand that supports additional operations, and can be passed directly to :class:Ligand.

from ties import Ligand


lig = Ligand('l02_same_atom_name.mol2')

# prepare the .mol2 input
lig.antechamber_prepare_mol2()

# the final .mol2 file
assert lig.current.exists()