Are you looking for the global minimum or an ensemble of conformers? Either
way, this is already very fast. Bear in mind, however, that MMFF’s accuracy
isn’t great for this type of tasks (see for example
https://arxiv.org/pdf/1705.04308.pdf ). In other words, I don’t see a use
case for generation of 10k or more conformers with MMFF. And super-fast
generation of large conformational ensembles for arbitrary molecules just
isn’t realistic.
Best,
Michal
On Wed, 18 Dec 2019 at 22:40, topgunhaides . <sunzhi....@gmail.com> wrote:
> Hi guys,
>
> Can anyone give me some advices to improve the efficiency of the embedding
> code? See example below:
>
>
> import time
> from rdkit import Chem
> from rdkit.Chem import AllChem
>
> suppl = Chem.SDMolSupplier('cid831548.sdf') # medium size molecule (10
> heavy atoms)
>
> for mol in suppl:
> mh = Chem.AddHs(mol, addCoords=True)
>
> # embedding
> start = time.time()
> AllChem.EmbedMultipleConfs(mh, numConfs=5000, maxAttempts=100,
> pruneRmsThresh=0.5,
> randomSeed=1, numThreads=0,
> enforceChirality=True,
> useExpTorsionAnglePrefs=True,
> useBasicKnowledge=True)
> cids = [conf.GetId() for conf in mh.GetConformers()]
> end = time.time()
> print("time eclipsed: ", end - start)
>
>
> The results:
> numConfs=1000, time eclipsed: 10 seconds
> numConfs=5000, time eclipsed: 66 seconds
> numConfs=10000, time eclipsed: 176 seconds
>
> I need to request a lot more than 10000 conformers per molecule and have a
> lot of molecules to process.
> I also wish to compute conformer energies and hopefully can do
> optimization (both are time consuming). So need to make my code as
> efficient as possible. Thank you!
>
> Best,
> Leon
>
>
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> Rdkit-discuss@lists.sourceforge.net
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>
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