https://github.com/baoilleach/deepsmiles

DeepSMILES - A variant of SMILES for use in machine-learning
https://github.com/baoilleach/deepsmiles

generative-models machine-learning neural-networks smiles

Last synced: 3 months ago
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DeepSMILES - A variant of SMILES for use in machine-learning

• Host: GitHub
• URL: https://github.com/baoilleach/deepsmiles
• Owner: baoilleach
• License: mit
• Created: 2018-09-18T09:20:23.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2021-05-24T08:07:54.000Z (about 5 years ago)
• Last Synced: 2025-05-11T20:42:59.741Z (about 1 year ago)
• Topics: generative-models, machine-learning, neural-networks, smiles
• Language: Python
• Size: 30.3 KB
• Stars: 137
• Watchers: 7
• Forks: 30
• Open Issues: 6
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE.txt

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README

          
DeepSMILES

==========

This Python module can convert well-formed SMILES (that is, as written by a cheminformatics toolkit) to DeepSMILES. It also does the reverse conversion.

Install the latest version with::

  pip install --upgrade deepsmiles

DeepSMILES is a SMILES-like syntax suited to machine learning. Rings are indicated using a single symbol instead of two, while branches do not use matching parentheses but rather use a right parenthesis as a 'pop' operator.

For example, benzene is `c1ccccc1` in SMILES but `cccccc6` in DeepSMILES (where the `6` indicates the ring size). As a branch example, the SMILES `C(Br)(OC)I` can be converted to the DeepSMILES `CBr)OC))I`. For more information, please see the corresponding preprint (https://doi.org/10.26434/chemrxiv.7097960.v1) or the lightning talk at https://www.slideshare.net/NextMoveSoftware/deepsmiles.

The library is used as follows:

.. code-block:: python

        import deepsmiles

        print("DeepSMILES version: %s" % deepsmiles.__version__)

        converter = deepsmiles.Converter(rings=True, branches=True)

        print(converter) # record the options used

        encoded = converter.encode("c1cccc(C(=O)Cl)c1")

        print("Encoded: %s" % encoded)

        try:

            decoded = converter.decode(encoded)

        except deepsmiles.DecodeError as e:

            decoded = None

            print("DecodeError! Error message was '%s'" % e.message)

        if decoded:

            print("Decoded: %s" % decoded)