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The directories 4-compute-qm-filtered and 4-compute-mm-filtered will then be used for the analysis below.

5. Schrodinger Optimization

General help about the Schrodinger command group:
openff-benchmark schrodinger --help

General comments

The schrodinger command group needs access to Schrodinger binaries. They will try to use the SCHRODINGER environment variable. If it is not set, the path to the Schrodinger binaries can be set in the --schrodinger-path command line option of the following commands.

Additionally, the OPLS force field makes use of custom parameters. The custom parameter directory can be set with the --opls-dir command line option.

The commands ffbuilder and optimize have the additional options to set --host and --max-jobs. With the --host option, you can specify the host (queue) on which the ffbuilder or optimization should be run. The name of the host has to be specified in your schrodinger.hosts configuration file. With --max-jobs, you can set the maximal number of parallel subjobs run on the host. If these options are not specified, default settings will be used.

OPLS3e vs OPLS4

Whether OPLS3e or OPLS4 is used, is automatically specified by the Schrodinger version you are using. If you use Schrodinger versions 2020-4 or below, the force field will be OPLS3e, if you use Schrodinger versions 2021-1 or above, the force field will be OPLS4.
If you ran the ffbuilder command for OPLS3e already, you can use the ffbuilder output to fit OPLS4 (not included in the openff-benchmark commands).

Step 1: Build custom parameters

Start up a ffbuilder custom parameter calculation using default arguments and the QM optimized molecules:

openff-benchmark schrodinger ffbuilder [--opls-dir ~/.schrodinger/opls_dir] 4-compute-qm/b3lyp-d3bj/dzvp/

It takes into account already available custom parameters in the path given as the option --opls-dir. If --opls-dir is not given or the specified path is not available (i.e. if you are a new user), all parameters will be calculated from scratch. If you run the ffbuilder for the first time and don't have custom parameters yet, do not specify the --opls-dir as this will lead to an error. The same counts if you used OPLS3e before and run the ffbuilder for the first time with OPLS4. The command will create a ffbuilder job ffb_openff_benchmark in the directory 7-schrodinger-ffb. If there are already output files in the output directory, they will be moved to a backup directory 7-schrodinger-ffb/ffb_openff_benchmark.bk[.x] and previously build custom parameters will be automatically merged with the custom parameter path. The output directory can be changed with the -o/--output-path option.

Now you have to wait until the ffbuilder job has finished. You can check the progress of the calculations in the file 7-schrodinger-ffb/ffb_openff_benchmark.log.

Note: You might realize that the ffbuilder input file ffb_input.sdf includes less conformers than you gave as an input. That is correct as the ffbuilder needs only one conformer per molecule.

Step 2: Merge parameters in custom parameter path

This command merges the newly built parameters to your custom parameter path.

openff-benchmark schrodinger ffmerge 7-schrodinger-ffb

The input path must be the output path of step 1. The custom parameters path can be specified with the option --opls-dir, which defaults to ~/.schrodinger/opls_dir/. If the specified or the default --opls-dir does not exist, the directory will be created and initialized. This could be the case if you are a new user or you want to create a separate custom parameter directory.

Step 3a: Run optimization without custom parameters

Optimization using OPLS3e using NO custom parameters:

openff-benchmark schrodinger optimize 4-compute-qm/b3lyp-d3bj/dzvp/

This will create a Schrodinger macromodel optimization run in the directory 8-schrodinger-mm-default. The latter directory can be changed with the -o/--output-path option. If the directory already exists and you want to replace the data, you need to run the command with the option --delete-existing.

Step 3b: Run optimization with custom parameters

By adding a custom parameter path to the optimize command, the optimization will use OPLS3e with custom parameters. Warning: If you have not built the custom parameters correctly and merged them to your custom parameter path, (steps 1 and 2), the command will use the available custom parameters, but the newly built parameters will be missing.

openff-benchmark schrodinger optimize --opls-dir ${HOME}/.schrodinger/opls_dir 4-compute-qm/b3lyp-d3bj/dzvp/

This will create a Schrodinger macromodel optimization run in the directory 9-schrodinger-mm-custom. The latter directory can be changed with the -o/--output-path option. If the directory already exists and you want to replace the data, you need to run the command with the option --delete-existing.

Step 4: Postprocessing

The output files mmod_output.maegz in the respective directories will be postprocessed with the commands:

openff-benchmark schrodinger postprocess -o 4-compute-mm 8-schrodinger-mm-default/mmod_output.maegz

and

openff-benchmark schrodinger postprocess -o 4-compute-mm 9-schrodinger-mm-custom/mmod_output.maegz

This will save the postprocessed SDF files in 4-compute-mm/opls3e_default/4-compute-mm/opls3e_custom (if you used Schrodinger versions 2020-4 or below) or in 4-compute-mm/opls4_default/4-compute-mm/opls4_custom (if you used Schrodinger versions 2021-1 or above). If these directories exist already and you want to replace the data, you need to run the commands with the option --delete-existing.

Hint:
The last two commands can be run together:
openff-benchmark schrodinger postprocess -o 4-compute-mm 8-schrodinger-mm-default/mmod_output.maegz 9-schrodinger-mm-custom/mmod_output.maegz
)

6. Analysis of results

Once all optimizations have finished, there are two ways to analyze the data. A compares the molecular-mechanics (MM) conformations and energies with the initial quantum-mechanics (QM) minimized conformation and energies, which was used as an input for the MM minimization. B searches for each QM conformation the closest MM conformation (based on RMSD), to ensure that similar conformations are compared. Optionally, a RMSD cut-off can be applied here.

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