One difference, if you care, is that the SMILES-based approach doesn’t
preserve any information about coordinates.
Andrew is providing further support for integrating this into the RDKit
itself. :-)
On Mon, 16 Apr 2018 at 08:30, Andrew Dalke <da...@dalkescientific.com>
wrote:
> On Apr 16, 2018, at 05:37, Patrick Walters <wpwalt...@gmail.com> wrote:
> >
> > Thanks Andrew, the SMILES approach seemed to have quite a few edge cases
> so I wrote something to work directly on a molecule.
>
> That's the approach I started with, until I figured out that it doesn't
> preserve chirality.
>
> If I change the end of your code to:
>
> ==========
> from mmpdblib import smiles_syntax
>
> def weld_dalke(core, r_groups):
> s1 = smiles_syntax.convert_labeled_wildcards_to_closures(core)
> s2 = smiles_syntax.convert_labeled_wildcards_to_closures(r_groups)
> return Chem.CanonSmiles(s1+"."+s2)
>
> if __name__ == "__main__":
> mol_to_weld = Chem.MolFromSmiles(
> "[*:1][C@](F)(Cl)O.N[*:1]")
> welded_mol = weld_r_groups(mol_to_weld)
> print("Expected :", Chem.CanonSmiles("N[C@](F)(Cl)O"))
> print("Direct :", Chem.MolToSmiles(welded_mol, isomericSmiles=True))
> print("Via SMILES:", weld_dalke("[*:1][C@](F)(Cl)O", "N[*:1]"))
> ==========
>
> These should print identical SMILES strings, but instead give:
>
> Expected : N[C@](O)(F)Cl
> Direct : N[C@@](O)(F)Cl
> Via SMILES: N[C@](O)(F)Cl
>
>
> If chirality preservation isn't a concern, then there's no problem.
>
> BTW, your current code assumes there will only be one attachment point on
> an atom. For example, the input
> [*:1][C@]([*:2])(Cl)O.N[*:1].F[*:2]
> create the output
> N.O[C](F)Cl
>
> It's not hard to fix, and I think more of a d'oh! issue.
>
>
> In a quick benchmark I put together just now, I found that my SMILES
> syntax manipulation approach was about twice as fast to turn the two
> core/R-group SMILES strings into a molecule.
>
> Cheers,
>
>
> Andrew
> da...@dalkescientific.com
>
>
>
>
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