Saving hydrophobic analyses#

Calculating, naming and persisting typed atom-pair proximity.

Store independently calculated observations with their source molecular system and retain their geometry, evaluated empty structures and original scientific references. A controlled fragment interface illustrates the workflow without claiming an energetic model.

Added in version 1.0.0.

Preparing declared chemistry and structures#

import molsysmt as msm
from rdkit import Chem
import numpy as np
from molsysmt import pyunitwizard as puw

molsys = msm.convert(Chem.MolFromSmiles('CCC.CCC'), to_form='molsysmt.MolSys')
xyz = np.array([[0,0,0], [.15,0,0], [.30,0,0], [0,.30,0], [.15,.30,0], [.30,.30,0]])
coordinates = np.repeat(xyz[None], 3, axis=0)
coordinates[1, 3:] += [0, 1., 0]
molsys.structures.append(coordinates=puw.quantity(coordinates, 'nm'))

Calculating and naming the interface#

Use disjoint fragment selections. Canonical roles are ordered source indices rather than ligand/protein labels; the evaluation scope retains both selections.

analysis = msm.interactions.hydrophobic.get_hydrophobic_interactions(
    molsys, selection=[0, 1, 2], selection_2=[3, 4, 5], selection_mode='between', pbc=False)
molsys.interactions = {**molsys.interactions, 'fragment_interface': analysis}
assert analysis.evaluated_structure_indices.tolist() == [0, 1, 2]
assert analysis.query(structure_indices=[1]).n_interactions == 0
print(analysis.participant_atoms, analysis.n_interactions)

[1 4] 2

Saving and loading#

Public conversion writes H5MSM 0.5. The round trip retains source axes, relation and occurrence identities, declared scope, producer versions and detached bibliography.

from pathlib import Path
from tempfile import TemporaryDirectory
with TemporaryDirectory() as directory:
    path = str(Path(directory) / 'interface.h5msm')
    msm.convert(molsys, to_form=path)
    loaded = msm.convert(path, to_form='molsysmt.MolSys')
restored = loaded.interactions['fragment_interface']
assert restored.parameters == analysis.parameters
assert restored.software == analysis.software
np.testing.assert_array_equal(restored.to_dict()['occurrence_indices'], analysis.to_dict()['occurrence_indices'])
print(restored.evaluated_structure_indices)

[0 1 2]

Extracting and reordering#

Select original atom and structure indices; extraction remaps all present domains and retains the requested structural order. Removing a participant removes its relation without rerunning detection.

subset = msm.extract(loaded, selection=[4, 1], structure_indices=[2, 0, 1])
assert subset.interactions['fragment_interface'].n_interactions == 2
print(subset.interactions['fragment_interface'].atom_source_indices)
print(subset.interactions['fragment_interface'].structure_source_indices)
removed = msm.extract(loaded, selection=[0, 1, 2])
assert removed.interactions['fragment_interface'].n_interactions == 0
print(removed.interactions['fragment_interface'].evaluated_structure_indices)

[1 4]
[2 0 1]
[0 1 2]