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QM ESP Training Set Selection and Generation

In general, the ESP data will be generated by the protocol proposed in the original AM1BCC publication as closely as possible [3].

Conformer Selection: The current plan is to employ the OpenEye ELF 10 implementation to generate reasonable conformers to include in the training set. This should produce conformers which do not contain strong electrostatic interactions. Roughly 10(???) A maximum of 5 conformers will be generated for each molecule in the training set where possible. Smaller or more rigid molecules may have less than this.

Level of Theory: Initially the ESPs will be generated at bothHF 6-31*G level theory and using PW6B95 + aug-cc-pV(D+d)Z (the level of theory suggested in the RESP2 publication [2]). This will allow us to explore somewhat whether including the physical property data begins to incorporate some of the overpolarisation qualities of HF but in a more ‘correct’ way.

ESP / EF Generation: If possible, the ESPs should The ESP and electric field data will be generated using the existing QC infrastructure.

The ESPs will be generated on a FCC grid , likely with a spacing close to of 0.5 and within a 1.4-2.0 shell around the molecule (although these settings should be checked to see if instead a coarser grid could be used without a big decrease in accuracy).

Lee-Ping Wang and Hyesu Jang have a large amount of experience here which should be drawn upon.

. These are the same settings used in the original AM1BCC paper.

Test Set Selection

The test set is to be curated by XtalPi, and this section will be updated with more details after further conversations with them.

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Task

Progress

Links

Assignee

The current AM1BCC parameters will need to be ported to the SMIRNOFF specification, and a new ParameterHandler will need to be created to

Status
colourPurple
titleCOMPLETE

Github link macro
linkhttps://github.com/SimonBoothroyd/am1bcc/tree/master/am1bccopenforcefield/openff-recharge

Simon Boothroyd

An automated way to reproducibly compute ESPs will need to be constructed if this does not already exist.

Status
colourPurple
titleCOMPLETE

Github link macro
linkhttps://github.com/openforcefield/openff-recharge/blob/master/scripts/pytorch/generate_esp.py

Simon Boothroyd

ForceBalance will need to be extended with a new target which can train the BCC parameters against the ESP data (possible consumed for QCArchive?) if this is not already possible.

Status
IN PROGRESS
colourYellowBlue
titleCOMPLETE

Github link macro
linkhttps://github.com/openforcefield/openff-recharge

Simon Boothroyd

The gradient calculations in OpenFF Evaluator need to be validated for computed gradients of BCC parameters.

Status
titleNOT STARTED

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