Page Comparison

Simpler Fits

Simple_fit1

Replacing t43, t44, t45 with an interpolated torsion parameter for the smarts pattern: “[*:1]~[#6X3:2]~[#6X3:3]~[*:4]” and fitting this FF to 170 targets from 14 datasets (listed below under fit0) that have a dihedral that matches this pattern. The objective function value is compared to the zeroth iteration of various other FFs and fits:

Fit7

With slight changes to Fit4, TIG0 is converted to an interpolated parameter, and TIG1a and TIG1b are removed. Number of targets 928. Starting parameters are from simple_fit1 and fit4 values. Here are the parameters optimized:

['TIG0', 'TIG1c', 'TIG1d', 'TIG2', 'TIG3', 'TIG4', 'TIG5a', 'TIG5b', 'TIG6', 'TIG7', 'TIG8'] - interpolated

Fit4: Parameters optimized

• ['TIG0', 'TIG1a', 'TIG1b'] - General torsions

• ['TIG1c', 'TIG1d', 'TIG2', 'TIG3', 'TIG4', 'TIG5a', 'TIG5b', 'TIG6', 'TIG7', 'TIG8'] - interpolated

On the training set the objective function values are:

Fit4.1: For each of the interpolated parameter a general torsion parameter is created where the central bond can be a single, aromatic or double bond (denoted by letters p,q,r at the end of parameter id). Due to lack of enough training data that match those patterns only a subset of those are trained and here are the parameters optimized.

Parameters optimized

• ['TIG0', ‘TIG1a', ‘TIG1b',
  ‘TIG3p’, ‘TIG3r', ‘TIG4p', ‘TIG5ap’, ‘TIG5bp’, ‘TIG1cp’, ‘TIG6p’, ‘TIG7p’, ‘TIG8p’, ‘TIG2p’, 'TIG2r’, 'TIG1dp’ ] - General torsions

Fit 0

Input FF:

...

• ['TIG0', 'TIG1a', 'TIG1b'] - General torsions

• ['TIG1c', 'TIG1d', 'TIG2', 'TIG3', 'TIG4', 'TIG5a', 'TIG5b', 'TIG6', 'TIG7', 'TIG8'] - interpolated

Targets:

1. 'Fragment Stability Benchmark'

2. 'OpenFF Gen 2 Torsion Set 1 Roche 2'

3. 'OpenFF Gen 2 Torsion Set 2 Coverage 2'

4. 'OpenFF Gen 2 Torsion Set 3 Pfizer Discrepancy 2'

5. 'OpenFF Gen 2 Torsion Set 4 eMolecules Discrepancy 2'

6. 'OpenFF Gen 2 Torsion Set 5 Bayer 2'

7. 'OpenFF Gen 2 Torsion Set 6 Supplemental 2'

8. 'OpenFF Group1 Torsions'

9. 'OpenFF Group1 Torsions 2'

10. 'OpenFF Group1 Torsions 3'

11. 'OpenFF Rowley Biaryl v1.0'

12. 'OpenFF Substituted Phenyl Set 1'

13. 'OpenFF-benchmark-ligand-fragments-v1.0'

14. 'SMIRNOFF Coverage Torsion Set 1'

...

Results of fits

For a first pass the objective function value didn’t look far away from 1.3.0. Some of the better looking TD curves are:

SMILES	QM Vs MM	Structure
COc1cccnc1-n1cccn1	Image Removed	Image Removed
CC(=O)Nc1cccs1	Image Removed	Image Removed
CN(C)c1ccccc1-c1ccccn1	Image Removed	Image Removed 0 (Iter 0 on TIG dataset)	5.9620E+03
Iter 0 with CN, or CC central bonds only
CN only TIGs [1a, 1c, 1d, 2, 6, 7, 8] + [t43, 44, 45]	5.4844E+03
CC only TIGs [0, 1b, 3, 4, 5a, 5b] + [t69, 69a, 76, 77, 78]	5.8771E+03

Fit0 is better than 1.3.0 from the objective function values in the above table. Among CN and CC central bonds, CN has a lower objective function value and thus effect of CC is more dominant on the overall objective function.

Comparing MM Fits 0, 3 and 1.3.0 with QM

Fit 0 with all the TIG* parameters, and fit 3 is the non-interpolated version i.e., interpolated TIG params split into single, double and aromatic terms, compared with 1.3.0_unconstrained, and QM data.

Comparison is done on the training set of molecules, removing the ones with in-ring torsions and sorting the table based on the average of absolute difference in conformer energies between QM and MM_fit0. A full list of molecules sorted in ascending order of (QM - MM_fit0) can be seen at https://github.com/MobleyLab/wbointerpolation/blob/main/compare_forcefields.ipynb

Here is a list of top 5 molecules that are in very good agreement with the QM energies for the fit0 interpolated parameters FF:

	Torsion ID	Avg. abs(QM - MM_fit0) kcal/mol	Avg. abs(QM - MM_fit3) kcal/mol	Avg. abs(QM - MM_1.3.0) kcal/mol	Chemical Structure	QM-MM relative energies
491	{'tid': '1762178', 'assigned_params': {'fit0': 'TIG3', 'fit3': 'TIG3p', 'openff_unconstrained-1.3.0': 't47'}}	0.023835	0.405296	0.866851	Image Added	Image Added
6	{'tid': '21272427', 'assigned_params': {'fit0': 'TIG4', 'fit3': 'TIG4p', 'openff_unconstrained-1.3.0': 't43'}}	0.051240	0.397015	0.125842	Image Added	Image Added
76	{'tid': '21272438', 'assigned_params': {'fit0': 'TIG5b', 'fit3': 'TIG5bp', 'openff_unconstrained-1.3.0': 't43'}}	0.062916	0.274251	0.597345	Image Added	Image Added
628	{'tid': '21272422', 'assigned_params': {'fit0': 'TIG5b', 'fit3': 'TIG5bp', 'openff_unconstrained-1.3.0': 't43'}}	0.070763	9.416926	0.761913	Image Added	Image Added
626	{'tid': '21540566', 'assigned_params': {'fit0': 'TIG4', 'fit3': 'TIG4p', 'openff_unconstrained-1.3.0': 't43'}}	0.075898	0.410239	0.109622	Image Added	Image Added

Here is a list of last 5 molecules that have a higher difference in averaged MM energy with fit0 compared to QM:

	Torsion ID	Avg. abs(QM - MM_fit0) kcal/mol	Avg. abs(QM - MM_fit3) kcal/mol	Avg. abs(QM - MM_1.3.0) kcal/mol	Chemical Structure	QM-MM relative energies
573	{'tid': '2703638', 'assigned_params': {'fit0': 'TIG3', 'fit3': 'TIG3p', 'openff_unconstrained-1.3.0': 't48'}}	5.264862	4.419863	4.908392	Image Added	Image Added
121	{'tid': '2703078', 'assigned_params': {'fit0': 'TIG2', 'fit3': 'TIG2r', 'openff_unconstrained-1.3.0': 't77'}}	5.694254	6.126509	6.142370	Image Added	Image Added
832	{'tid': '4269709', 'assigned_params': {'fit0': 'TIG3', 'fit3': 'TIG3p', 'openff_unconstrained-1.3.0': 't43'}}	6.086503	8.061331	6.024023	Image Added	Image Added
812	{'tid': '21272420', 'assigned_params': {'fit0': 'TIG4', 'fit3': 'TIG4p', 'openff_unconstrained-1.3.0': 't47'}}	6.263980	6.102699	6.772570	Image Added	Image Added
532	{'tid': '19953581', 'assigned_params': {'fit0': 'TIG3', 'fit3': 'TIG3p', 'openff_unconstrained-1.3.0': 't43'}}	6.369817	7.591619	5.529416	Image Added	Image Added