Skip to main content

No project description provided

Reason this release was yanked:

Non-maintainer uploaded package to pypi without coordinating with maintainers, pypi package ownership was transferred amicably to maintainers. Pypi releases of openforcefield software may be available at a later date, but issues with unavailable dependencies need to be resolved first.

Project description

Fragmenter

Test Status Documentation Status codecov License: MIT Software DOI Paper DOI

A package for fragmenting molecules for quantum mechanics torsion scans.

More information about using this package and its features can be found in the documentation.

Warning: This code is currently experimental and under active development. If you are using this code, be aware that it is not guaranteed to provide the correct results, and the API can change without notice.

Installation

The package and its dependencies can be installed using the conda package manager:

conda install -c conda-forge openff-fragmenter

Getting Started

We recommend viewing the getting started example in a Jupyter notebook. This full example can be found here.

Here will will show how a drug-like molecule can be fragmented using this framework, and how those fragments can be easily visualised using its built-in helper utilities.

To begin with we load in the molecule to be fragmented. Here we load Cobimetinib directly using its SMILES representation using the Open Force Field toolkit:

from openff.toolkit.topology import Molecule

parent_molecule = Molecule.from_smiles(
    "OC1(CN(C1)C(=O)C1=C(NC2=C(F)C=C(I)C=C2)C(F)=C(F)C=C1)[C@@H]1CCCCN1"
)

Next we create the fragmentation engine which will perform the actual fragmentation. Here we will use the recommended WBOFragmenter with default options:

from openff.fragmenter.fragment import WBOFragmenter

frag_engine = WBOFragmenter()
# Export the engine's settings directly to JSON
frag_engine.json()

Use the engine to fragment the molecule:

result = frag_engine.fragment(parent_molecule)
# Export the result directly to JSON
result.json()

Any generated fragments will be returned in a FragmentationResult object. We can loop over each of the generated fragments and print both the SMILES representation of the fragment as well as the map indices of the bond that the fragment was built around:

for fragment in result.fragments:
    print(f"{fragment.bond_indices}: {fragment.smiles}")

Finally, we can visualize the produced fragments:

from openff.fragmenter.depiction import depict_fragmentation_result

depict_fragmentation_result(result=result, output_file="example_fragments.html")

Copyright

Copyright (c) 2018, Chaya D. Stern

Acknowledgements

Project based on the Computational Molecular Science Python Cookiecutter version 1.5.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

openff_fragmenter-0.2.2.tar.gz (53.3 kB view details)

Uploaded Source

File details

Details for the file openff_fragmenter-0.2.2.tar.gz.

File metadata

  • Download URL: openff_fragmenter-0.2.2.tar.gz
  • Upload date:
  • Size: 53.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.13

File hashes

Hashes for openff_fragmenter-0.2.2.tar.gz
Algorithm Hash digest
SHA256 bbca471098bd9093815f70ce085e6f01f664660cc3395274f40d655f01689b54
MD5 89b3ee36041c33dee48ad15b121e4e47
BLAKE2b-256 0a824ca6d42ddf9086b214e74649c9fb467df8a61e12fe4ec2f34bb62962afe6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page