Determination of the relative binding free energies of peptide inhibitors to the HIV-1 protease

1991 ◽  
Vol 34 (8) ◽  
pp. 2654-2659 ◽  
Author(s):  
David M. Ferguson ◽  
Randall J. Radmer ◽  
Peter A. Kollman
Keyword(s):  
Peptide Inhibitors ◽  
Free Energies ◽  
Relative Binding ◽  
Hiv 1 ◽  
Binding Free Energies

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 Computing Clinically Relevant Binding Free Energies of HIV-1 Protease Inhibitors

2014 ◽  
Vol 10 (3) ◽  
pp. 1228-1241 ◽  
Author(s):  
David W. Wright ◽  
Benjamin A. Hall ◽  
Owain A. Kenway ◽  
Shantenu Jha ◽  
Peter V. Coveney
Keyword(s):  
Protease Inhibitors ◽  
Free Energies ◽  
Hiv 1 ◽  
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.

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