Charge-Changing Perturbations and Path Sampling via Classical Molecular Dynamic Simulations of Simple Guest–Host Systems

Öhlknecht, Christoph; Perthold, Jan Walther; Lier, Bettina; Oostenbrink, Chris

doi:10.1021/acs.jctc.0c00719

Cited by 19 publications

(41 citation statements)

References 62 publications

(143 reference statements)

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“…Interestingly, the other two perturbations involving a charge change result in slightly different free-energy differences. It is important to note that such perturbation calculations suffer from various artifacts, including one related with the choice of the cutoff scheme used in simulations (the DSM term in ref ( 66 )). As different cutoff schemes were used when simulating with the two simulation packages (group-based and atom-based for GROMOS and GROMACS), contributing differently to the abovementioned artifact, the observed discrepancies in the free-energy differences are not surprising.…”

Section: Resultsmentioning

confidence: 99%

Perturbation Free-Energy Toolkit: An Automated Alchemical Topology Builder

Petrov

2021

J. Chem. Inf. Model.

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Free-energy calculations play an important role in the application of computational chemistry to a range of fields, including protein biochemistry, rational drug design, or materials science. Importantly, the free-energy difference is directly related to experimentally measurable quantities such as partition and adsorption coefficients, water activity, and binding affinities. Among several techniques aimed at predicting free-energy differences, perturbation approaches, involving the alchemical transformation of one molecule into another through intermediate states, stand out as rigorous methods based on statistical mechanics. However, despite the importance of free-energy calculations, the applicability of the perturbation approaches is still largely impeded by a number of challenges, including the definition of the perturbation path, i.e., alchemical changes leading to the transformation of one molecule to the other. To address this, an automatic perturbation topology builder based on a graph-matching algorithm is developed, which can identify the maximum common substructure (MCS) of two or multiple molecules and provide the perturbation topologies suitable for free-energy calculations using the GROMOS and the GROMACS simulation packages. Various MCS search options are presented leading to alternative definitions of the perturbation pathway. Moreover, perturbation topologies generated using the default multistate MCS search are used to calculate the changes in free energy between lysine and its two post-translational modifications, 3-methyllysine and acetyllysine. The pairwise free-energy calculations performed on this test system led to a cycle closure of 0.5 ± 0.3 and 0.2 ± 0.2 kJ mol –1 , with GROMOS and GROMACS simulation packages, respectively. The same relative free energies between the three states are obtained by employing the enveloping distribution sampling (EDS) approach when compared to the pairwise perturbations. Importantly, this toolkit is made available online as an open-source Python package ( ).

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Section: Resultsmentioning

confidence: 99%

Perturbation Free-Energy Toolkit: An Automated Alchemical Topology Builder

Petrov

2021

J. Chem. Inf. Model.

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“…However, it has been observed that the binding free energy computed with path sampling did not converge to the same end result as those done alchemically and corrected with the Rocklin correction. 49 However, one study has also shown that they can give similar results. 50 One explanation for this discrepancy would be that the self-interaction term would be size-dependent when the species of opposite charge cannot sample the same configurational space.…”

Section: Discussionmentioning

confidence: 91%

Correction Schemes for Absolute Binding Free Energies Involving Lipid Bilayers

Biggin

2022

J. Chem. Theory Comput.

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Absolute binding free-energy (ABFE) calculations are playing an increasing role in drug design, especially as they can be performed on a range of disparate compounds and direct comparisons between them can be made. It is, however, especially important to ensure that they are as accurate as possible, as unlike relative binding free-energy (RBFE) calculations, one does not benefit as much from a cancellation of errors during the calculations. In most modern implementations of ABFE calculations, a particle mesh Ewald scheme is typically used to treat the electrostatic contribution to the free energy. A central requirement of such schemes is that the box preserves neutrality throughout the calculation. There are many ways to deal with this problem that have been discussed over the years ranging from a neutralizing plasma with a post hoc correction term through to a simple co-alchemical ion within the same box. The post hoc correction approach is the most widespread. However, the vast majority of these studies have been applied to a soluble protein in a homogeneous solvent (water or salt solution). In this work, we explore which of the more common approaches would be the most suitable for a simulation box with a lipid bilayer within it. We further develop the idea of the so-called Rocklin correction for lipid-bilayer systems and show how such a correction could work. However, we also show that it will be difficult to make this generalizable in a practical way and thus we conclude that the use of a “co-alchemical ion” is the most useful approach for simulations involving lipid membrane systems.

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“…In the SAMPL7 TrimerTrip host-guest blind challenge, utilization of the AMOEBA force field shows excellent results with 7/8 samples having errors within 2 kcal/mol ( Laury et al, 2018 ; Shi et al, 2020 ; Amezcua et al, 2021 ). The commonly used approach to maintain charge neutrality through co-alchemical ions is shown not to fully eliminate charge artifacts in periodic simulation boxes due to localized differences in electrostatic potentials and solvent densities for the distant ion and bound ligand ( Ohlknecht et al, 2020b ). Continuum-electrostatics calculations ( Ohlknecht et al, 2020a ) and the “Warp-Drive” ( Ekimoto et al, 2018 ) method of simultaneously perturbing the protein-ligand complex and a distant unbound ligand are proposed to more accurately correct for finite-size effects.…”

Section: Free Energy Calculation Approachesmentioning

confidence: 99%

Recent Developments in Free Energy Calculations for Drug Discovery

King

Aitchison

et al. 2021

Front. Mol. Biosci.

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The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.

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Charge-Changing Perturbations and Path Sampling via Classical Molecular Dynamic Simulations of Simple Guest–Host Systems

Cited by 19 publications

References 62 publications

Perturbation Free-Energy Toolkit: An Automated Alchemical Topology Builder

Perturbation Free-Energy Toolkit: An Automated Alchemical Topology Builder

Correction Schemes for Absolute Binding Free Energies Involving Lipid Bilayers

Recent Developments in Free Energy Calculations for Drug Discovery

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