Expanded Ensemble Methods Can be Used to Accurately Predict Protein-Ligand Relative Binding Free Energies

2021 ◽  
Vol 17 (10) ◽  
pp. 6536-6547
Author(s):  
Si Zhang ◽  
David F. Hahn ◽  
Michael R. Shirts ◽  
Vincent A. Voelz
Keyword(s):  
Ensemble Methods ◽  
Free Energies ◽  
Relative Binding ◽  
Binding Free Energies ◽  
Expanded Ensemble

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>

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>

scholarly journals Implicit ligand theory for relative binding free energies

2018 ◽  
Vol 148 (10) ◽  
pp. 104114 ◽  
Author(s):  
Trung Hai Nguyen ◽  
David D. L. Minh
Keyword(s):  
Free Energies ◽  
Relative Binding ◽  
Binding Free Energies

scholarly journals D3R Grand Challenge 2: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies

2017 ◽  
Vol 32 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Zied Gaieb ◽  
Shuai Liu ◽  
Symon Gathiaka ◽  
Michael Chiu ◽  
Huanwang Yang ◽  
...  
Keyword(s):  
Grand Challenge ◽  
Free Energies ◽  
Blind Prediction ◽  
Relative Binding ◽  
Binding Free Energies

scholarly journals Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility

2021 ◽  
Author(s):  
Alexander Wade ◽  
Agastya Bhati ◽  
Shunzhou Wan ◽  
Peter Coveney
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Binding Free Energy ◽  
Thermodynamic Integration ◽  
Free Energy Perturbation ◽  
Free Energies ◽  
Ensemble Averaging ◽  
Relative Binding ◽  
Energy Perturbation ◽  
Binding Free Energies

The binding free energy between a ligand and its target protein is an essential quantity to know at all stages of the drug discovery pipeline. Assessing this value computationally can offer insight into where efforts should be focused in the pursuit of effective therapeutics to treat myriad diseases. In this work we examine the computation of alchemical relative binding free energies with an eye to assessing reproducibility across popular molecular dynamics packages and free energy estimators. The focus of this work is on 54 ligand transformations from a diverse set of protein targets: MCL1, PTP1B, TYK2, CDK2 and thrombin. These targets are studied with three popular molecular dynamics packages: OpenMM, NAMD2 and NAMD3. Trajectories collected with these packages are used to compare relative binding free energies calculated with thermodynamic integration and free energy perturbation methods. The resulting binding free energies show good agreement between molecular dynamics packages with an average mean unsigned error between packages of 0.5 $kcal/mol$ The correlation between packages is very good with the lowest Spearman's, Pearson's and Kendall's tau correlation coefficient between two packages being 0.91, 0.89 and 0.74 respectively. Agreement between thermodynamic integration and free energy perturbation is shown to be very good when using ensemble averaging.

scholarly journals Polyomaviridae Assembly Polymorphism from an Energy Landscape Perspective

2008 ◽  
Vol 9 (3-4) ◽  
pp. 245-256 ◽  
Author(s):  
Karim M. ElSawy ◽  
Leo S. D. Caves ◽  
Reidun Twarock
Keyword(s):  
Calcium Ions ◽  
Computational Analysis ◽  
Binding Free Energy ◽  
Energy Landscape ◽  
Free Energies ◽  
Experimental Conditions ◽  
Relative Binding ◽  
Disulfide Linkages ◽  
Binding Free Energies

Polyomaviridae assemblein vitrointo different aggregates depending on experimental conditions. We use an energy landscape approach using empirical energy calculations to quantify how the formation of these different aggregates depends on pH, the presence of bound calcium ions and disulfide linkages. Computations are carried out for SV40, a member of the Polyomaviridae family and are based on the binding free energy landscape of three distinct trimers of pentamers that correspond to the different bonding configurations between the capsid proteins observed in its crystal structure. Our computational analysis shows that the energetics of one of these environments is pivotal for the polymorphic assembly behaviour of SV40, whilst the binding energy landscapes of the other two environments are broadly funnel-shaped and thus contribute little to the formation of particles other than virus-like particles (VLP). We have quantified how the existence of bound calcium ions in the absence of disulfide linkages enhances the binding free energies of all three environments and hence, favours the assembly of VLPs. Moreover, estimation of the relative binding free energies of the three environments at pH 5 and pH 8 reveals that they are destabilized at pH 5 relative to pH 8. The extent of this destabilization is dependent on the presence of disulfide linkages and bound calcium ions and accounts for the experimentally observed polymorphic behaviour of VP1 proteins at pH 5. Interestingly, concurrent existence of bound calcium ions and disulfide linkages is found to be destabilizing and thus may disrupt the assembly of VLPs at pH 8.

Accurate Calculation of Relative Binding Free Energies between Ligands with Different Net Charges

2018 ◽  
Vol 14 (12) ◽  
pp. 6346-6358 ◽  
Author(s):  
Wei Chen ◽  
Yuqing Deng ◽  
Ellery Russell ◽  
Yujie Wu ◽  
Robert Abel ◽  
...  
Keyword(s):  
Free Energies ◽  
Accurate Calculation ◽  
Relative Binding ◽  
Net Charges ◽  
Binding Free Energies
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