python-repository-hub / cmiles

Generate canonical molecule identifiers for quantum chemistry database

CMILES is no longer actively maintained

As of May 2021, CMILES is no longer being actively maintained. Most of its essential functionality has been migrated to the Open Force Field Toolkit and QCSubmit packages.

API points that handle former CMILES functions in these packages include:

• openff.toolkit.toplogy.Molecule.to_smiles with the mapped=True keyword argument
• openff.toolkit.topology.Molecule.from_mapped_smiles
• openff.toolkit.topology.Molecule.from_qcschema
• And the openff-qcsubmit dataset class

cmiles

Generate canonical identifiers for chemical databases, specifically quantum chemical data.

cmiles seeks to address several issues:

1. Link the QC molecule to its cheminformatics molecular graph to make QC data useful to the force field and machine learning communities.
   A QC molecule is identified by its elements and geometry. Each conformer is considered a separate molecule. However, from a cheminformatics perspective, the connectivity graph is the identity of the molecule.

2. Canonical identifiers.
   When indexing a chemical database, it is crucial that the identifier is canonical to reduce redundancy and search failures.
   Problem:
   Each toolkit has its own canonicalization algorithm. This algorithm may change in different versions of the toolkit.
   Solution:
   Distribute cmiles as a Docker image with pinned dependencies.

3. Canonical order of QC geometry.
   Since QC molecules are identified by their elements and geometry, canonical atomic order can reduce redundancy.
   Problem:
   In cheminformatics toolkits, the order of atoms in a molecular graph are arbitrary. Therefore, every time you generate a new molecular graph, the order of the atoms can change.
   Solution:
   Use the toolkits canonical atomic ranking to generate a SMILES string that has explicit hydrogens and map indices that correspond to the canonical atomic ranking. Then, this mapped SMILES can be used as a SMARTS pattern to find the mapping of a molecular graph's these map indices to atomic indices. This map is then used to generate canonical order for the xyz coordinates and symbols in the QC molecule. cmiles.utils provides functions that will do this.
   In addition, the mapped SMILES ensure that all molecular graphs generated can be mapped to QC geometries if those geometries are in the order of the map.

4. Standardize compounds
   Provide an index to find all protomers of a molecule.
   Problem:
   Different protomeric states are different QC molecules. However, sometimes all protomers and / tautomers of a molecule are needed. SMILES strings are different for each protomer. While InChI standardizes molecular charge states, it only standardize the tautomers it recognizes and not others. Some tautomers it does not capture are keto-enol and enamine-imine.

   cmiles does not yet offer a full solution. Currently it provides the InChI, the unique protomer from openeye and MolStandardize from rdkit. rdkit's solution only addresses tautomers of the same charge states and openeye's solution does not capture indoles, isoindoles and some mesomers. However, the union of these identifiers captures more than each individual solution.

How to use cmiles

cmiles has one main function, to_molecule_id(molecule) This function returns a dictionary with 10 identifiers generated with either OpenEye or RDKit.

1. Canonical SMILES
2. Canonical, isomeric SMILES
3. Canonical, isomeric, explicit hydrogen SMILES
4. Canonical, explicit hydrogen SMILES
5. Canonical, isomeric, explicit hydrogen, mapped SMILES.
6. Molecular formula in Hill notation
7. InChI
8. InChIKey
9. unique protomer SMILES
10. Standardized tautomer SMILES

cmiles.utils provides functions to generate atom maps and map ordered geometries.

Dependencies

One of the following cheminformatics toolkits:

• openeye
• rdkit

Copyright

Copyright (c) 2018, Chaya D. Stern

Acknowledgements

Project based on the Computational Chemistry Python Cookiecutter