openforcefield/openforcefields: Version 1.3.0 "Parsley" Update

Wagner, Jeff; Thompson, Matt; Dotson, David; hyejang,; Rodríguez-Guerra, Jaime

doi:10.5281/zenodo.4118484

“…This training data curation 46 resulted in significant improvement in relative conformer energies, optimized geometries, and torsional profiles with respect to accurate high-level ab initio data when compared to Parsley 1.0.0. Revisions after Parsley 1.2.0 include new torsion parameters for dialkyl amides in Parsley 1.3.0 to improve amide torsional energy profiles; 47 in Parsley 1.3.1, a minor regression in the accuracy of the description of sulfonamides was corrected. 48 Building on the foundation of Open Force Field Parsley generation of force fields, we now introduce the OpenFF Sage 2.0.0 small molecule force field which builds on earlier work and extends it by refitting the LJ parameters.…”

Section: Openff Innovations: Journey From Parsley To Sagementioning

confidence: 99%

Development and Benchmarking of Open Force Field 2.0.0 — the Sage Small Molecule Force Field

Boothroyd¹,

Behara

²

,

Madin

³

et al. 2022

Preprint

View full text Add to dashboard Cite

We introduce the Open Force Field (OpenFF)~2.0.0 small molecule force field for drug-like molecules, code-named Sage, which builds upon our previous iteration, Parsley. OpenFF force fields are based on direct chemical perception, which generalizes easily to highly diverse sets of chemistries based on substructure queries. Like the previous OpenFF iterations, the Sage generation of OpenFF force fields was validated in protein-ligand simulations to be compatible with AMBER biopolymer force fields. In this paper we detail the methodology used to develop this force field, as well as the innovations and improvements introduced since the release of Parsley 1.0.0. One particularly significant feature of Sage is a set of improved Lennard-Jones (LJ) parameters retrained against condensed phase mixture data, the first refit of LJ parameters in the OpenFF small molecule force field line. Sage also includes valence parameters refit to a larger database of quantum chemical calculations than previous versions, as well as improvements in how this fitting is performed. Force field benchmarks show improvements in general metrics of performance against quantum chemistry reference data such as root mean square deviations (RMSD) of optimized conformer geometries, torsion fingerprint deviations (TFD), and improved relative conformer energetics (ΔΔ𝐸). We present a variety of benchmarks for these metrics against our previous force fields as well as in some cases other small molecule biomolecular force fields. Sage also demonstrates improved performance in estimating physical properties, including comparison against experimental data from various thermodynamic databases for small molecule properties such as Δ𝐻_𝑚𝑖𝑥, ρ(𝑥), Δ𝐺_𝑠𝑜𝑙𝑣 and Δ𝐺_𝑡𝑟𝑎𝑛𝑠. Additionally, we benchmarked against protein-ligand binding free energies (Δ𝐺_𝑏𝑖𝑛𝑑), where Sage yields results statistically similar to previous force fields. All the data is made publicly available along with complete details on how to reproduce the training results at https://github.com/openforcefield/openff-sage.

show abstract

“…Importantly, it also yields highly competitive accuracy in calculations of relative protein-ligand binding free energies. This work lays a foundation for efficient iterative force field improvement, which is already underway in subsequent releases (OpenFF 1.1, 1.2, 1.2.1 and 1.3, [37][38][39][40][41] to be described elsewhere). This work could also be naturally extended to automatically derive molecule-specific (i.e.…”

Section: Conclusion and Directionsmentioning

confidence: 99%

“…Importantly, the infrastructure described here establishes a foundation for going far beyond Parsley, through the ongoing creation of a series of continually improving, open, small molecule force fields. The process reported here in the OpenFF 1.0.0 release continues in subsequent releases (OpenFF 1.1, 1.2 and 1.3) [37][38][39][40][41] which will be described in follow-up work.…”

Section: Introductionmentioning

confidence: 99%

Development and Benchmarking of Open Force Field v1.0.0, the Parsley Small Molecule Force Field

Qiu¹,

Smith²,

Boothroyd³

et al. 2021

Preprint

View full text Add to dashboard Cite

We present a methodology for defining and optimizing a general force field for classical molecular simulations, and we describe its use to derive the Open Force Field 1.0.0 small molecule force field, code-named Parsley. Rather than traditional atom-typing, our approach builds on the SMIRKS-native Open Force Field (SMIRNOFF) parameter assignment formalism, which handles increases in the diversity and specificity of the force field definition without needlessly increasing the complexity of the specification. Parameters are optimized with the ForceBalance tool, based on reference quantum chemical data that include torsion potential energy profiles, optimized gas-phase structures, and vibrational frequencies. These quantum reference data are computed and are maintained with QCArchive, an open-source and freely available distributed computing and database software ecosystem. In this initial application of the method, we present essentially a full optimization of all valence parameters and report tests of the resulting force field against compounds and data types outside the training set. These tests show improvements in optimized geometries and conformational energetics and demonstrate that Parsley's accuracy for liquid properties is similar to that of other general force fields, as is accuracy on binding free energies. We find that this initial Parsley force field affords accuracy similar to that of other general force fields when used to calculate relative binding free energies spanning 199 protein-ligand systems. Additionally, the resulting infrastructure allows us to rapidly optimize an entire new force field with minimal human intervention.

show abstract

“…Importantly, it also yields highly competitive accuracy in calculations of relative protein-ligand binding free energies. This work lays a foundation for efficient iterative force field improvement, which is already underway in subsequent releases (OpenFF 1.1, 1.2, 1.2.1 and 1.3, [37][38][39][40][41] to be described elsewhere). In the near term, we aim to extend the optimization to nonbonded interaction parameters and incorporate expanded training and testing data sets.…”

Section: Conclusion and Directionsmentioning

confidence: 99%

“…Importantly, the infrastructure described here establishes a foundation for going far beyond Parsley, through the the ongoing creation of a series of continually improving, open, small molecule force fields. The process reported here in the OpenFF 1.0.0 release continues in subsequent releases (OpenFF 1.1, 1.2 and 1.3) [37][38][39][40][41] which will be described in follow-up work.…”

Section: Introductionmentioning

confidence: 99%

Development and Benchmarking of Open Force Field v1.0.0, the Parsley Small Molecule Force Field

Qiu¹,

Smith²,

Boothroyd³

et al. 2021

Preprint

View full text Add to dashboard Cite

We present a methodology for defining and optimizing a general force field for classical molecular simulations, and we describe its use to derive the Open Force Field 1.0.0 small molecule force field, code-named Parsley. Rather than traditional atom-typing, our approach builds on the SMIRKS-native Open Force Field (SMIRNOFF) parameter assignment formalism, which handles increases in the diversity and specificity of the force field definition without needlessly increasing the complexity of the specification. Parameters are optimized with the ForceBalance tool, based on reference quantum chemical data that include torsion potential energy profiles, optimized gas-phase structures, and vibrational frequencies. These quantum reference data are computed and are maintained with QCArchive, an open-source and freely available distributed computing and database software ecosystem. In this initial application of the method, we present essentially a full optimization of all valence parameters and report tests of the resulting force field against compounds and data types outside the training set. These tests show improvements in optimized geometries and conformational energetics and demonstrate that Parsley's accuracy for liquid properties is similar to that of other general force fields, as is accuracy on binding free energies. We find that this initial Parsley force field affords accuracy similar to that of other general force fields when used to calculate relative binding free energies spanning 199 protein-ligand systems. Additionally, the resulting infrastructure allows us to rapidly optimize an entire new force field with minimal human intervention.

show abstract

openforcefield/openforcefields: Version 1.3.0 "Parsley" Update

Cited by 7 publications

References 0 publications

Development and Benchmarking of Open Force Field 2.0.0 — the Sage Small Molecule Force Field

Development and Benchmarking of Open Force Field 2.0.0 — the Sage Small Molecule Force Field

Development and Benchmarking of Open Force Field v1.0.0, the Parsley Small Molecule Force Field

Development and Benchmarking of Open Force Field v1.0.0, the Parsley Small Molecule Force Field

Contact Info

Product

Resources

About