scholarly journals Binding free energies for the SAMPL8 CB8 “Drugs of Abuse” challenge from umbrella sampling combined with Hamiltonian replica exchange

2022 ◽  
Author(s):  
Daniel Markthaler ◽  
Hamzeh Kraus ◽  
Niels Hansen
Keyword(s):  
Drugs Of Abuse ◽  
Binding Free Energy ◽  
Correction Term ◽  
Quantitative Agreement ◽  
Umbrella Sampling ◽  
Replica Exchange ◽  
Free Energies ◽  
Guest Molecules ◽  
Hamiltonian Replica Exchange ◽  
Binding Free Energies

AbstractUmbrella sampling along a one-dimensional order parameter in combination with Hamiltonian replica exchange was employed to calculate the binding free energy of five guest molecules with known affinity to cucurbit[8]uril. A simple empirical approach correcting for the overestimation of the affinity by the GAFF force field was proposed and subsequently applied to the seven guest molecules of the “Drugs of Abuse” SAMPL8 challenge. Compared to the uncorrected binding free energies, the systematic error decreased but quantitative agreement with experiment was only reached for a few compounds. From a retrospective analysis a weak point of the correction term was identified.

scholarly journals A replica exchange umbrella sampling (REUS) approach to predict host–guest binding free energies in SAMPL8 challenge

2021 ◽  
Author(s):  
Mahdi Ghorbani ◽  
Phillip S. Hudson ◽  
Michael R. Jones ◽  
Félix Aviat ◽  
Rubén Meana-Pañeda ◽  
...  
Keyword(s):  
Free Energy ◽  
Binding Free Energy ◽  
Umbrella Sampling ◽  
Free Energy Calculations ◽  
Replica Exchange ◽  
Free Energies ◽  
Guest Binding ◽  
Binding Free Energy Calculations ◽  
Force Field Parameters ◽  
Binding Free Energies

AbstractIn this study, we report binding free energy calculations of various drugs-of-abuse to Cucurbit-[8]-uril as part of the SAMPL8 blind challenge. Force-field parameters were obtained from force-matching with different quantum mechanical levels of theory. The Replica Exchange Umbrella Sampling (REUS) approach was used with a cylindrical restraint to enhance the sampling of host–guest binding. Binding free energy was calculated by pulling the guest molecule from one side of the symmetric and cylindrical host, then into and through the host, and out the other side (bidirectional) as compared to pulling only to the bound pose inside the cylindrical host (unidirectional). The initial results with force-matched MP2 parameter set led to RMSE of 4.68 $${\text{kcal}}/{\text{mol}}$$ kcal / mol from experimental values. However, the follow-up study with CHARMM generalized force field parameters and force-matched PM6-D3H4 parameters resulted in RMSEs from experiment of $$2.65$$ 2.65 and $$1.72 {\text{kcal}}/{\text{mol}}$$ 1.72 kcal / mol , respectively, which demonstrates the potential of REUS for accurate binding free energy calculation given a more suitable description of energetics. Moreover, we compared the free energies for the so called bidirectional and unidirectional free energy approach and found that the binding free energies were highly similar. However, one issue in the bidirectional approach is the asymmetry of profile on the two sides of the host. This is mainly due to the insufficient sampling for these larger systems and can be avoided by longer sampling simulations. Overall REUS shows great promise for binding free energy calculations.

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 ◽  
...  
Keyword(s):  
Free Energy ◽  
First Principles ◽  
Binding Free Energy ◽  
Free Energy Perturbation ◽  
Free Energies ◽  
Hamiltonian Replica Exchange ◽  
Current State ◽  
Energy Perturbation ◽  
Binding Free Energies ◽  
Non Equilibrium

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.

scholarly journals Energy–entropy method using multiscale cell correlation to calculate binding free energies in the SAMPL8 host–guest challenge

2021 ◽  
Author(s):  
Hafiz Saqib Ali ◽  
Arghya Chakravorty ◽  
Jas Kalayan ◽  
Samuel P. de Visser ◽  
Richard H. Henchman
Keyword(s):  
Free Energy ◽  
Drugs Of Abuse ◽  
Binding Free Energy ◽  
Average Error ◽  
Scoring Functions ◽  
Vibrational Entropy ◽  
Free Energies ◽  
Energy Entropy ◽  
Wide Range ◽  
Binding Free Energies

AbstractFree energy drives a wide range of molecular processes such as solvation, binding, chemical reactions and conformational change. Given the central importance of binding, a wide range of methods exist to calculate it, whether based on scoring functions, machine-learning, classical or electronic structure methods, alchemy, or explicit evaluation of energy and entropy. Here we present a new energy–entropy (EE) method to calculate the host–guest binding free energy directly from molecular dynamics (MD) simulation. Entropy is evaluated using Multiscale Cell Correlation (MCC) which uses force and torque covariance and contacts at two different length scales. The method is tested on a series of seven host–guest complexes in the SAMPL8 (Statistical Assessment of the Modeling of Proteins and Ligands) “Drugs of Abuse” Blind Challenge. The EE-MCC binding free energies are found to agree with experiment with an average error of 0.9 kcal mol−1. MCC makes clear the origin of the entropy changes, showing that the large loss of positional, orientational, and to a lesser extent conformational entropy of each binding guest is compensated for by a gain in orientational entropy of water released to bulk, combined with smaller decreases in vibrational entropy of the host, guest and contacting water.

scholarly journals Automation of absolute protein-ligand binding free energy calculations for docking refinement and compound evaluation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germano Heinzelmann ◽  
Michael K. Gilson
Keyword(s):  
Free Energy ◽  
Early Stage ◽  
Binding Free Energy ◽  
Low Cost ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Drug Candidates ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

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.

scholarly journals Alchemical Absolute Protein-Ligand Binding Free Energies for Drug Design

2021 ◽  
Author(s):  
Yuriy Khalak ◽  
Gary Tresdern ◽  
Matteo Aldeghi ◽  
Hannah Magdalena Baumann ◽  
David L. Mobley ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Drug Design ◽  
Ligand Binding ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

The recent advances in relative protein-ligand binding free energy calculations have shown the value of alchemical methods in drug discovery. Accurately assessing absolute binding free energies, although highly desired, remains...

scholarly journals Hit-to-lead and lead optimization binding free energy calculations for G protein-coupled receptors

2020 ◽  
Vol 10 (6) ◽  
pp. 20190128 ◽  
Author(s):  
Shunzhou Wan ◽  
Andrew Potterton ◽  
Fouad S. Husseini ◽  
David W. Wright ◽  
Alexander Heifetz ◽  
...  
Keyword(s):  
G Protein ◽  
Binding Free Energy ◽  
Absolute Error ◽  
Free Energy Calculations ◽  
Lead Optimization ◽  
Receptor Protein ◽  
Enhanced Sampling ◽  
Free Energies ◽  
G Protein Coupled ◽  
Binding Free Energies

We apply the hit-to-lead ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and lead-optimization TIES (thermodynamic integration with enhanced sampling) methods to compute the binding free energies of a series of ligands at the A 1 and A 2A adenosine receptors, members of a subclass of the GPCR (G protein-coupled receptor) superfamily. Our predicted binding free energies, calculated using ESMACS, show a good correlation with previously reported experimental values of the ligands studied. Relative binding free energies, calculated using TIES, accurately predict experimentally determined values within a mean absolute error of approximately 1 kcal mol −1 . Our methodology may be applied widely within the GPCR superfamily and to other small molecule–receptor protein systems.

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