scholarly journals Accurate absolute free energies for ligand–protein binding based on non-equilibrium approaches

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Vytautas Gapsys ◽  
Ahmet Yildirim ◽  
Matteo Aldeghi ◽  
Yuriy Khalak ◽  
David van der Spoel ◽  
...  

AbstractThe accurate calculation of the binding free energy for arbitrary ligand–protein pairs is a considerable challenge in computer-aided drug discovery. Recently, it has been demonstrated that current state-of-the-art molecular dynamics (MD) based methods are capable of making highly accurate predictions. Conventional MD-based approaches rely on the first principles of statistical mechanics and assume equilibrium sampling of the phase space. In the current work we demonstrate that accurate absolute binding free energies (ABFE) can also be obtained via theoretically rigorous non-equilibrium approaches. Our investigation of ligands binding to bromodomains and T4 lysozyme reveals that both equilibrium and non-equilibrium approaches converge to the same results. The non-equilibrium approach achieves the same level of accuracy and convergence as an equilibrium free energy perturbation (FEP) method enhanced by Hamiltonian replica exchange. We also compare uni- and bi-directional non-equilibrium approaches and demonstrate that considering the work distributions from both forward and reverse directions provides substantial accuracy gains. In summary, non-equilibrium ABFE calculations are shown to yield reliable and well-converged estimates of protein–ligand binding affinity.

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.


2020 ◽  
Vol 20 (12) ◽  
pp. 1179-1187
Author(s):  
K. Kumar Reddy ◽  
R.S. Rathore ◽  
P. Srujana ◽  
R.R. Burri ◽  
C. Ravikumar Reddy ◽  
...  

Background: The accurate ranking of analogs of lead molecules with respect to their estimated binding free energies to drug targets remains highly challenging in molecular docking due to small relative differences in their free energy values. Methods: Free energy perturbation (FEP) method, which provides the most accurate relative binding free energy values were earlier used to calculate free energies of many ligands for several important drug targets including Fructose-1,6-BisphosPhatase (FBPase). The availability of abundant structural and experimental binding affinity data for FBPase inhibitors provided an ideal system to evaluate four widely used docking programs, AutoDock, Glide, GOLD and SurflexDock, distinct from earlier comparative evaluation studies. Results: The analyses suggested that, considering various parameters such as docking pose, scoring and ranking accuracy, sensitivity analysis and newly introduced relative ranking score, Glide provided reasonably consistent results in all respects for the system studied in the present work. Whereas GOLD and AutoDock also demonstrated better performance, AutoDock results were found to be significantly superior in terms of scoring accuracy compared to the rest. Conclusion: Present analysis serves as a useful guide for researchers working in the field of lead optimization and for developers in upgradation of the docking programs.


2013 ◽  
Vol 19 (26) ◽  
pp. 4674-4686 ◽  
Author(s):  
R.S. Rathore ◽  
M. Sumakanth ◽  
M. Reddy ◽  
P. Reddanna ◽  
Allam Rao ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germano Heinzelmann ◽  
Michael K. Gilson

AbstractAbsolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies. We also show that it is practical to carry out these calculations cheaply by using graphical processing units in common machines that can be built for this purpose. The combination of automation and low cost positions this procedure to be applied in a relatively high-throughput mode and thus stands to enable new applications in early-stage drug discovery.


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