combinemols3d 1.1.0

Combine 2 molecules in 3D by sample.

CombineMols3D

Combine 2 molecules in 3D by sample.

Overview of the combination process.

How it works?

In short, it could be summarized into 2 steps:

1. Translation:
   • The new bond length is determined by the summation of the covalent radii of the two atoms.
   • Set one atom as the central of a sphere, sample positions on this sphere and calculate the repulsion between the new addon to the whole molecule. (The repulsion is measured by the summation of the inverse distance.)
   • Choose the minimum repulsion position and translate the whole addon molecule as a rigid body.
2. Rotation:
   • Set the bonded site as center and the nearest neighbor as rotation axes. Rotate the addon molecule as a rigid body
   • Sample rotation angles to minimize the repulsion between the addon molecule to the main molecule. (Again, the repulsion is measured by the summation of the inverse distance.)
   • Choose the minimum repulsion image and this is the final combination state.

Install

pip install combinemols3d

Usage

1. Prepare your to-be-bonded molecules as ase.Atoms object. (Read ase documentation for format manipulation.)
2. Determine which sites to be bonded together. (dummy sites)
3. Combine them by eliminate the dummy sites.

from ase.visualize import view
from ase.build.molecule import molecule
from combinemols3d.CombineMols3D import combine_2_mols_with_dummy, combine_2_mols

main_mol = molecule('C7NH5')
sub_mol = molecule('BDA')

view(main_mol)
view(sub_mol)

final_mol = combine_2_mols_with_dummy(molecule_1=main_mol.copy(), molecule_2=sub_mol.copy(),
                                      dummy_atom_index_1=11, dummy_atom_index_2=6)
view(final_mol)

If you don't want to eliminate the dummy sites, use the combine_2_mols instead:

final_mol = combine_2_mols(molecule_1=main_mol, molecule_2=sub_mol,
                                      tgt_atom_1_index=11, tgt_atom_2_index=6)
view(final_mol)

Other parameters are same for the two functions:

• Conformation related:

  • skin: to get a proper bond length for the new bond. Here we adopt the covalent radii method. A skin parameter is added to finetune the bond length, though it is 0 by default.

    $R(\mathrm{AB})=r(\mathrm{A})+r(\mathrm{B})+skin$

  • cutoff_mult: there are several places to detect neighbors for a specific atom. By default, it is natural cutoff as follow equation:

    $DetectRange(\mathrm{AB})=r(\mathrm{A})+r(\mathrm{B})+0.3$

    We can enlarge our search scope to multiply the natural cutoff as follow equation:

    $DetectRange(\mathrm{AB})=cutoff mult*(r(\mathrm{A})+r(\mathrm{B})+0.3)$

• Performance related:

  • sample_times: how many times to sample addon positions in translation and angles in rotation.
  • rotation_times: In the rotation stage, we will rotate the whole addon molecule as a rigid body. The orientations of the addon site to its neighbors are taken as fixed rotation axes. How many neighbors to be considered could be performance critical.

Note

Contact me: [e-mail]