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Think about adding `templating` when generating TS guesses

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#33 0 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
25/100
Tipo de issue
Nueva funcionalidad
Claridad
Necesita aclaración
Estado de actividad
Estancado
Stack tecnológico
python
Área
backend

Línea de trabajo

No implementation file, test, or entry point is named. Start by locating the code that generates transition-state guesses and compare its current approach with the templating workflow described in the issue and paper. Done means the scope and design are established, including template matching and atom correspondence.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

From reading about other tools, many will template when generating a TS guess. From the AutoTS paper

In addition to interpolation, we have the ability to use geometric information from a previously located TS. We refer to this approach as templating and to the predefined TS geometries as templates. TS templates, along with the reactant and product geometries that they connect (as verified by an IRC calculation), are stored in an auxiliary computer file. Several string representations of the input reaction are generated and used to search this template file for matching reactions. Each representation is of a particular order, i, and is constructed by generating SMILES strings for the atoms in the reaction center plus all (i – 1)th nearest neighbors. We tend to use only three orders starting with i = 1. The SMILES patterns of the reactant and product structures are combined with the symbol “≫” as in reaction SMILES. The algorithm has the preference for matches at the highest order attainable.
Once it is recognized that a usable template exists, we extract it from the file and compute an atom correspondence between the input structures and template structures. This is done by utilizing an MCS algorithm, which computes a bijection for the reaction center atoms. The reaction matching described above guarantees that the reaction center and possibly some number of neighbors make up a substructure shared between the reactant and product.

Lenguaje dominante
Python
Estrellas
51
Forks
19
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Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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