SCINE Chemoton

Philosophy of SCINE Chemoton

Chemoton is an open-source, extensible framework for explorations of chemical reaction mechanisms based on the first principles of quantum mechanics. It enables reaction network explorations for a wide range of chemical problems, with applications in mechanism elucidation, reaction path optimization, retrosynthetic path validation, reagent design, and microkinetic modeling. Chemoton puts a key focus on general applicability, i.e., avoiding any restrictions to specific chemical systems. This is possible thanks to the stringent first-principles basis of all algorithms in our framework.

Technical Details

Chemoton is implemented as a Python module. Its purpose is to drive the entire machinery for automated chemical reaction network exploration. This is done by means of two major objects, so-called engines and gears. Engines execute the same action over and over again (e.g., the creation of new conformers). Gears are specific algorithms with are invoked by the individual engines (for example, conformers could be created by a gear implementing explicit enumeration of all possible structures, or by a different gear relying on molecular dynamics).
An important feature when exploring chemical reaction networks is a possibility to tame the combinatorial explosion of potential reactive events. To this end, Chemoton implements a wide range of filters (for example, limiting the maximum size molecules are allowed to have). These filters can be freely combined by logical "and" and "or" operators and can be further customized by the users.
To keep track of an exploration, Chemoton stores all important information in a MongoDB, the access to which is simplified by means of the SCINE database wrapper. To advance the exploration, Chemoton sets up a large number of calculations, which are also stored in this database. The calculations are then carried out by SCINE Puffin.

Current Features

  • Scriptable framework with a base set of features for the automated exploration of chemical reaction networks; these networks consist of
    • structures, aggregated into compounds,
    • flasks (aggregates of stable non-bonded complexes),
    • elementary steps, aggregated into reactions,
    • properties, tagged to structures, and
    • calculations that generated the network
  • Engines with perpetually running gears to continuously perform certain tasks:
    • Basic bookkeeping jobs:
      • Sorting structures into compounds
      • Sorting elementary steps into reactions
      • Basic scheduling and prioritization of calculations
    • Data completion jobs:
      • Conformer generation
      • Hessian generation for transition states and minimum energy structures
      • Rerun failed calculations
    • Elementary step exploration
      • Based on atoms/fragments (AFIR, NT1)
      • Based on bonds (NT2)
      • Based on reaction templates, implemented by SCINE Art
    • Steering of network growth via kinetic analyses (SCINE KiNetX) or reaction path analyses (Pathfinder)
  • Filters to steer and limit explorations
    • Filter compounds based on element counts, atom counts, molecular weight, composition, etc.
    • Filter reactive sites based on atom types, custom user rules, etc.

Download

SCINE Chemoton is distributed as an open source code. Visit our GitHub page to download it.

Future Releases

  • Improve kinetic modeling

Documentation

Documentation is provided in the source code; you can also access it here.

Support

Despite intense testing of the program, questions may arise with respect to the usage of SCINE Chemoton. Do not hesitate to contact the developers via scine@phys.chem.ethz.ch in case of any questions and suggestions.

References

  • Primary reference for Chemoton 4.0.0:
    M. Bensberg, S. A. Grimmel, L. Lang, G. N. Simm, J.-G. Sobez, M. Steiner, P. L. Türtscher, J. P. Unsleber, T. Weymuth, M. Reiher, "qcscine/chemoton: Release 4.0.0 (Version 4.0.0)", Zenodo, 2024. DOI
  • Please cite also the following paper when publishing results obtained with Chemoton:
    J. P. Unsleber, S. A. Grimmel, M. Reiher, "Chemoton 2.0: Autonomous Exploration of Chemical Reaction Networks", J. Chem. Theory Comput., 2022, 18, 5393. DOI
  • Reference for Chemoton 1.0.0:
    G. N. Simm, M. Reiher, "Context-Driven Exploration of Complex Chemical Reaction Networks", J. Chem. Theory Comput., 2017, 13, 6108. DOI