Building of TSs with reactant and product species geometries

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
25/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
python
Domain
tooling

Research direction

Start with the proposed entry points autotst.reaction and autotst.conformer.systematic, then review how optimized geometries, bounds matrices, and conformer analysis are currently handled. The work is done when optimized reactant and product geometries can be read or generated with a warning, TS construction uses tighter bounds for bound atoms, and conformer analysis covers rotatable torsions without cis/trans bonds or chiral centers.

Written by the indexing model from the issue text.

Description

Conformational changes like inversion of chiral centers and rotation about double bonds rarely occur when reactants go to TSs (e.g. a reactant containing a cis double bond will probably have a TS with that corresponding double bond being cis). This is similar to the templating idea proposed in #33, but with a variation. I'm proposing that we do the following when building a TS geometry:

  1. Read in QM optimized geometries, if they exist, for reactants and products.
  2. Perform conformer analysis and QM optimization for reactants and products that have no optimized geometries and read them in.
  3. Using optimized geometries for reactants and products, construct a TS geometry using a tighter bounds matrix for bound atoms (because we trust these values)
  4. Perform a conformer analysis on rotatable torsions only because cis/trans bonds and chiral centers probably won't invert.

This would require us to do the following:

  • Create a database of optimized geometries for autotst.reaction to read from
    • Possibly build the geometry with RDKit if a reactant or product geometry isn't available but post a warning.
  • Revise the way the bounds matrix is edited in autotst.reaction
  • Revise the conformer analysis in autotst.conformer.systematic to not include cit/trans bonds and chiral centers
Dominant language
Python
Stars
51
Forks
19
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