Solvation Free Energies of Small Amides and Amines from Molecular Dynamics/Free Energy Perturbation Simulations Using Pairwise Additive and Many-Body Polarizable Potentials

1995 ◽  
Vol 99 (29) ◽  
pp. 11575-11583 ◽  
Author(s):  
Yanbo Ding ◽  
Dan N. Bernardo ◽  
Karsten Krogh-Jespersen ◽  
Ronald M. Levy
2010 ◽  
Vol 6 (5) ◽  
pp. 1509-1519 ◽  
Author(s):  
Devleena Shivakumar ◽  
Joshua Williams ◽  
Yujie Wu ◽  
Wolfgang Damm ◽  
John Shelley ◽  
...  

2021 ◽  
Author(s):  
Alexander Wade ◽  
Agastya Bhati ◽  
Shunzhou Wan ◽  
Peter Coveney

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.


2018 ◽  
Author(s):  
Filip Fratev ◽  
Thomas Steinbrecher ◽  
Svava Ósk Jónsdóttir

AbstractEstimating the correct binding modes of ligands in protein-ligand complexes is not only crucial in the drug discovery process, but also for elucidating potential toxicity mechanisms. In the current paper, we discuss and demonstrate a computational modelling protocol using the combination of docking, classical (cMD) and accelerated (aMD) molecular dynamics and free energy perturbation (FEP+ protocol) for identification of the binding modes of selected perfluorocarboxyl acids (PFCAs) in the PPARγ nuclear receptor.Initially, we employed both the regular and induced fit docking which failed to correctly predict the ligand binding modes and rank the compounds with respect to experimental free energies of binding, when they were docked into non-native X-ray structure. The cMD and aMD simulations identified the presence of multiple binding modes for these compounds, and the shorter chain PFCAs (C6-C8) continuously moved between a few energetically favourable binding conformations. These results demonstrate that the docking scoring function cannot rank compounds precisely in such cases, not due to its insufficiency, but because of the use of incorrect or only one unique bindings pose, neglecting the protein dynamics. Finally, based on MD predictions of binding conformations, the FEP+ sampling protocol was extended and then accurately reproduced experimental differences in the free energies. Thus, the preliminary MD simulations can also provide helpful information about correct set-up of the FEP+ calculations. These results show that the PFCAs binding modes were accurately predicted and the FEP+ protocol can be used to estimate free energies of binding of flexible molecules outside of typical drug-like compounds.Our in silico workflow revealed the main characteristics of the PFCAs, which are week PPARγ partial agonists and illustrated the importance of specific ligand-residue interactions within the LBD. This work also suggests a common workflow for identification of ligand binding modes, ligand-protein dynamics description and relative free energy calculations.


2019 ◽  
Vol 21 (25) ◽  
pp. 13826-13834 ◽  
Author(s):  
Piero Procacci

Free energy perturbation (FEP) approaches with stratification have seen widespread and increasing use in computational studies of biologically relevant molecules.


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