scholarly journals Improving the description of interactions between Ca2+ and protein carboxylate groups, including γ-carboxyglutamic acid: revised CHARMM22* parameters

RSC Advances ◽  
2015 ◽  
Vol 5 (83) ◽  
pp. 67820-67828 ◽  
Author(s):  
Andrew T. Church ◽  
Zak E. Hughes ◽  
Tiffany R. Walsh
Keyword(s):  
Force Field ◽  
Free Energies ◽  
Carboxylate Groups ◽  
Carboxyglutamic Acid ◽  
Binding Free Energies

We show that the CHARMM22* force-field over-binds the interaction between aqueous carboxylates and Ca2+, and introduce a modification that can recover experimentally-determined binding free energies for these systems.

scholarly journals Binding thermodynamics of host-guest systems with SMIRNOFF99Frosst 1.0.5 from the Open Force Field Initiative

2019 ◽  
Author(s):  
David Slochower ◽  
Niel Henriksen ◽  
Lee-Ping Wang ◽  
John Chodera ◽  
David Mobley ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Force Field ◽  
Small Molecule ◽  
Force Fields ◽  
Free Energy Calculations ◽  
Model Systems ◽  
Conformational Space ◽  
Free Energies ◽  
Binding Thermodynamics ◽  
Binding Free Energies

<div><div><div><p>Designing ligands that bind their target biomolecules with high affinity and specificity is a key step in small- molecule drug discovery, but accurately predicting protein-ligand binding free energies remains challenging. Key sources of errors in the calculations include inadequate sampling of conformational space, ambiguous protonation states, and errors in force fields. Noncovalent complexes between a host molecule with a binding cavity and a drug-like guest molecules have emerged as powerful model systems. As model systems, host-guest complexes reduce many of the errors in more complex protein-ligand binding systems, as their small size greatly facilitates conformational sampling, and one can choose systems that avoid ambiguities in protonation states. These features, combined with their ease of experimental characterization, make host-guest systems ideal model systems to test and ultimately optimize force fields in the context of binding thermodynamics calculations.</p><p><br></p><p>The Open Force Field Initiative aims to create a modern, open software infrastructure for automatically generating and assessing force fields using data sets. The first force field to arise out of this effort, named SMIRNOFF99Frosst, has approximately one tenth the number of parameters, in version 1.0.5, compared to typical general small molecule force fields, such as GAFF. Here, we evaluate the accuracy of this initial force field, using free energy calculations of 43 α and β-cyclodextrin host-guest pairs for which experimental thermodynamic data are available, and compare with matched calculations using two versions of GAFF. For all three force fields, we used TIP3P water and AM1-BCC charges. The calculations are performed using the attach-pull-release (APR) method as implemented in the open source package, pAPRika. For binding free energies, the root mean square error of the SMIRNOFF99Frosst calculations relative to experiment is 0.9 [0.7, 1.1] kcal/mol, while the corresponding results for GAFF 1.7 and GAFF 2.1 are 0.9 [0.7, 1.1] kcal/mol and 1.7 [1.5, 1.9] kcal/mol, respectively, with 95% confidence ranges in brackets. These results suggest that SMIRNOFF99Frosst performs competitively with existing small molecule force fields and is a parsimonious starting point for optimization.</p></div></div></div>

scholarly journals Computation of protein–ligand binding free energies using quantum mechanical bespoke force fields

MedChemComm ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 1116-1120 ◽  
Author(s):  
Daniel J. Cole ◽  
Israel Cabeza de Vaca ◽  
William L. Jorgensen
Keyword(s):  
Ligand Binding ◽  
Force Field ◽  
Molecular Mechanics ◽  
Force Fields ◽  
Quantum Mechanical ◽  
T4 Lysozyme ◽  
Free Energies ◽  
Binding Free Energies

A quantum mechanical bespoke molecular mechanics force field is derived for the L99A mutant of T4 lysozyme and used to compute absolute binding free energies of six benzene analogs to the protein.

scholarly journals Calculating binding free energies of host–guest systems using the AMOEBA polarizable force field

2016 ◽  
Vol 18 (44) ◽  
pp. 30261-30269 ◽  
Author(s):  
David R. Bell ◽  
Rui Qi ◽  
Zhifeng Jing ◽  
Jin Yu Xiang ◽  
Christopher Mejias ◽  
...  
Keyword(s):  
Force Field ◽  
Free Energies ◽  
Polarizable Force Field ◽  
Guest Binding ◽  
Binding Free Energies

Cucurbit[7]uril host–guest binding free energies are investigated using the AMOEBA polarizable force field.

scholarly journals Binding thermodynamics of host-guest systems with SMIRNOFF99Frosst 1.0.5 from the Open Force Field Initiative

2019 ◽  
Author(s):  
David Slochower ◽  
Niel Henriksen ◽  
Lee-Ping Wang ◽  
John Chodera ◽  
David Mobley ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Force Field ◽  
Small Molecule ◽  
Force Fields ◽  
Free Energy Calculations ◽  
Model Systems ◽  
Conformational Space ◽  
Free Energies ◽  
Binding Thermodynamics ◽  
Binding Free Energies

<div><div><div><p>Designing ligands that bind their target biomolecules with high affinity and specificity is a key step in small- molecule drug discovery, but accurately predicting protein-ligand binding free energies remains challenging. Key sources of errors in the calculations include inadequate sampling of conformational space, ambiguous protonation states, and errors in force fields. Noncovalent complexes between a host molecule with a binding cavity and a drug-like guest molecules have emerged as powerful model systems. As model systems, host-guest complexes reduce many of the errors in more complex protein-ligand binding systems, as their small size greatly facilitates conformational sampling, and one can choose systems that avoid ambiguities in protonation states. These features, combined with their ease of experimental characterization, make host-guest systems ideal model systems to test and ultimately optimize force fields in the context of binding thermodynamics calculations.</p><p><br></p><p>The Open Force Field Initiative aims to create a modern, open software infrastructure for automatically generating and assessing force fields using data sets. The first force field to arise out of this effort, named SMIRNOFF99Frosst, has approximately one tenth the number of parameters, in version 1.0.5, compared to typical general small molecule force fields, such as GAFF. Here, we evaluate the accuracy of this initial force field, using free energy calculations of 43 α and β-cyclodextrin host-guest pairs for which experimental thermodynamic data are available, and compare with matched calculations using two versions of GAFF. For all three force fields, we used TIP3P water and AM1-BCC charges. The calculations are performed using the attach-pull-release (APR) method as implemented in the open source package, pAPRika. For binding free energies, the root mean square error of the SMIRNOFF99Frosst calculations relative to experiment is 0.9 [0.7, 1.1] kcal/mol, while the corresponding results for GAFF 1.7 and GAFF 2.1 are 0.9 [0.7, 1.1] kcal/mol and 1.7 [1.5, 1.9] kcal/mol, respectively, with 95% confidence ranges in brackets. These results suggest that SMIRNOFF99Frosst performs competitively with existing small molecule force fields and is a parsimonious starting point for optimization.</p></div></div></div>

scholarly journals Expanded Ensemble Methods Can Be Used to Accurately Predict Protein-Ligand Relative Binding Free Energies

2021 ◽  
Author(s):  
Si Zhang ◽  
David Hahn ◽  
Michael R. Shirts ◽  
Vincent Voelz
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Ensemble Methods ◽  
Free Energy Calculation ◽  
Energy Calculation ◽  
Free Energies ◽  
Relative Binding ◽  
Alchemical Free Energy ◽  
Binding Free Energies ◽  
Expanded Ensemble

<p>Alchemical free energy methods have become indispensable in computational drug discovery for their ability to calculate highly accurate estimates of protein-ligand affinities. Expanded ensemble (EE) methods, which involve single simulations visiting all of the alchemical intermediates, have some key advantages for alchemical free energy calculation. However, there have been relatively few examples published in the literature of using expanded ensemble simulations for free energies of protein-ligand binding. In this paper, as a test of expanded ensemble methods, we computed relative binding free energies using the Open Force Field Initiative force field (codename “Parsley”) for twenty-four pairs of Tyk2 inhibitors derived from a congeneric series of 16 compounds. The EE predictions agree well with the experimental values (RMSE of 0.94 ± 0.13 kcal mol<sup>−1</sup> and MUE of 0.75 ± 0.12 kcal mol<sup>−1</sup>). We find that while increasing the number of alchemical intermediates can improve the phase space overlap, faster convergence can be obtained with fewer intermediates, as long as the acceptance rates are sufficient. We find that convergence can be improved using more aggressive updating of the biases, and that estimates can be improved by performing multiple independent EE calculations. This work demonstrates that EE is a viable option for alchemical free energy calculation. We discuss the implications of these findings for rational drug design, as well as future directions for improvement.</p>

Validation of AMBER/GAFF for Relative Free Energy Calculations

2019 ◽  
Author(s):  
Lin Song ◽  
Tai-Sung Lee ◽  
Chun Zhu ◽  
Darrin M. York ◽  
Kenneth M. Merz Jr.
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Free Energy Calculations ◽  
Enhanced Sampling ◽  
Free Energies ◽  
Data Set ◽  
Relative Free Energy ◽  
Relative Binding ◽  
Sampling Approach ◽  
Binding Free Energies

We computed relative binding free energies using GPU accelerated Thermodynamic Integration (GPU-TI) on a dataset originally assembled by Schrödinger, Inc.. Using their GPU enabled free energy code (FEP+) and the OPLS2.1 force field combined with REST2 enhanced sampling approach, these authors obtained an overall MUE of 0.9 kcal/mol and an overall RMSD of 1.14 kcal/mol.<b> </b>In our study using GPU-TI of AMBER with the AMBER14SB/GAFF1.8 force field but without enhanced sampling, we obtained an overall MUE of 1.17 kcal/mol and an overall RMSD of 1.50 kcal/mol for the 330 mutations contained in this data set.

Binding thermodynamics of host-guest systems with SMIRNOFF99Frosst 1.0.5 from the Open Force Field Initiative

2019 ◽  
Author(s):  
David Slochower ◽  
Niel Henriksen ◽  
Lee-Ping Wang ◽  
John Chodera ◽  
David Mobley ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Force Field ◽  
Small Molecule ◽  
Force Fields ◽  
Free Energy Calculations ◽  
Model Systems ◽  
Conformational Space ◽  
Free Energies ◽  
Binding Thermodynamics ◽  
Binding Free Energies

<div><div><div><p>Designing ligands that bind their target biomolecules with high affinity and specificity is a key step in small- molecule drug discovery, but accurately predicting protein-ligand binding free energies remains challenging. Key sources of errors in the calculations include inadequate sampling of conformational space, ambiguous protonation states, and errors in force fields. Noncovalent complexes between a host molecule with a binding cavity and a drug-like guest molecules have emerged as powerful model systems. As model systems, host-guest complexes reduce many of the errors in more complex protein-ligand binding systems, as their small size greatly facilitates conformational sampling, and one can choose systems that avoid ambiguities in protonation states. These features, combined with their ease of experimental characterization, make host-guest systems ideal model systems to test and ultimately optimize force fields in the context of binding thermodynamics calculations.</p><p><br></p><p>The Open Force Field Initiative aims to create a modern, open software infrastructure for automatically generating and assessing force fields using data sets. The first force field to arise out of this effort, named SMIRNOFF99Frosst, has approximately one tenth the number of parameters, in version 1.0.5, compared to typical general small molecule force fields, such as GAFF. Here, we evaluate the accuracy of this initial force field, using free energy calculations of 43 α and β-cyclodextrin host-guest pairs for which experimental thermodynamic data are available, and compare with matched calculations using two versions of GAFF. For all three force fields, we used TIP3P water and AM1-BCC charges. The calculations are performed using the attach-pull-release (APR) method as implemented in the open source package, pAPRika. For binding free energies, the root mean square error of the SMIRNOFF99Frosst calculations relative to experiment is 0.9 [0.7, 1.1] kcal/mol, while the corresponding results for GAFF 1.7 and GAFF 2.1 are 0.9 [0.7, 1.1] kcal/mol and 1.7 [1.5, 1.9] kcal/mol, respectively, with 95% confidence ranges in brackets. These results suggest that SMIRNOFF99Frosst performs competitively with existing small molecule force fields and is a parsimonious starting point for optimization.</p></div></div></div>

scholarly journals Expanded Ensemble Methods Can Be Used to Accurately Predict Protein-Ligand Relative Binding Free Energies

2021 ◽  
Author(s):  
Si Zhang ◽  
David Hahn ◽  
Michael R. Shirts ◽  
Vincent Voelz
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Ensemble Methods ◽  
Free Energy Calculation ◽  
Energy Calculation ◽  
Free Energies ◽  
Relative Binding ◽  
Alchemical Free Energy ◽  
Binding Free Energies ◽  
Expanded Ensemble

<p>Alchemical free energy methods have become indispensable in computational drug discovery for their ability to calculate highly accurate estimates of protein-ligand affinities. Expanded ensemble (EE) methods, which involve single simulations visiting all of the alchemical intermediates, have some key advantages for alchemical free energy calculation. However, there have been relatively few examples published in the literature of using expanded ensemble simulations for free energies of protein-ligand binding. In this paper, as a test of expanded ensemble methods, we computed relative binding free energies using the Open Force Field Initiative force field (codename “Parsley”) for twenty-four pairs of Tyk2 inhibitors derived from a congeneric series of 16 compounds. The EE predictions agree well with the experimental values (RMSE of 0.94 ± 0.13 kcal mol<sup>−1</sup> and MUE of 0.75 ± 0.12 kcal mol<sup>−1</sup>). We find that while increasing the number of alchemical intermediates can improve the phase space overlap, faster convergence can be obtained with fewer intermediates, as long as the acceptance rates are sufficient. We find that convergence can be improved using more aggressive updating of the biases, and that estimates can be improved by performing multiple independent EE calculations. This work demonstrates that EE is a viable option for alchemical free energy calculation. We discuss the implications of these findings for rational drug design, as well as future directions for improvement.</p>

Validation of AMBER/GAFF for Relative Free Energy Calculations

2019 ◽  
Author(s):  
Lin Song ◽  
Tai-Sung Lee ◽  
Chun Zhu ◽  
Darrin M. York ◽  
Kenneth M. Merz Jr.
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Free Energy Calculations ◽  
Enhanced Sampling ◽  
Free Energies ◽  
Data Set ◽  
Relative Free Energy ◽  
Relative Binding ◽  
Sampling Approach ◽  
Binding Free Energies

We computed relative binding free energies using GPU accelerated Thermodynamic Integration (GPU-TI) on a dataset originally assembled by Schrödinger, Inc.. Using their GPU enabled free energy code (FEP+) and the OPLS2.1 force field combined with REST2 enhanced sampling approach, these authors obtained an overall MUE of 0.9 kcal/mol and an overall RMSD of 1.14 kcal/mol.<b> </b>In our study using GPU-TI of AMBER with the AMBER14SB/GAFF1.8 force field but without enhanced sampling, we obtained an overall MUE of 1.17 kcal/mol and an overall RMSD of 1.50 kcal/mol for the 330 mutations contained in this data set.

Sign in / Sign up

Export Citation Format

Share Document