Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes via Nonequilibrium Candidate Monte Carlo

Gill, Samuel C.; Lim, Nathan M.; Grinaway, Patrick; Rustenburg, Ariën S.; Fass, Josh; Ross, Gregory A.; Chodera, John D.; Mobley, David L.

doi:10.1021/acs.jpcb.7b11820

Cited by 77 publications

(164 citation statements)

References 107 publications

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“…Using 100 ns per λ window and the most abundant conformation,

ΔΔ G_{2}^{°}

equals 31.6 ± 2.5 kJ/mol which combined with the polarization cost of

normalΔ G_{1, 3}^{0}

results in

ΔΔ G_{italicrx, 1}^{o} = 21.3 \pm 4.3

kJ/mol. Combining this value with the Boltzmann weight of this most representative conformation yields

ΔΔ G_{rx}^{o} = ΔΔ G_{italicrx, 1}^{o} + italicRT \ln ω_{1} = 20.2 \pm 4.3

kJ/mol according to Gill et al…”

Section: Resultsmentioning

confidence: 99%

Conformational sampling and polarization of Asp26 in pK_a calculations of thioredoxin

Gomez

Vöhringer‐Martinez

2019

Proteins

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Thioredoxin is a protein that has been used as model system by various computational methods to predict the pKa of aspartate residue Asp26 which is 3.5 units higher than a solvent exposed one (eg, Asp20). Here, we use extensive atomistic molecular dynamics simulations of two different protonation states of Asp26 in combination with conformational analysis based on RMSD clustering and principle component analysis to identify representative conformations of the protein in solution. For each conformation, the Gibbs free energy of proton transfer between Asp26 and Asp20, which is fully solvated in a loop region of the protein, is calculated with the Amber99sb force field in alchemical transformations. The varying polarization of the two residues in different molecular environments and protonation states is described by Hirshfeld‐I (HI) atomic charges obtained from the averaged polarized electron density. Our results show that the Gibbs free energy of proton transfer is dependent on the protein conformation, the proper sampling of the neighboring Lys57 residue orientations and on water molecules entering the hydrophobic cavity upon deprotonating Asp26. The inclusion of the polarization of both aspartate residues in the free energy cycle by HI atomic charges corrects the results from the non‐polarizable force field and reproduces the experimental ΔpKa value of Asp26.

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“…Using 100 ns per λ window and the most abundant conformation,

ΔΔ G_{2}^{°}

equals 31.6 ± 2.5 kJ/mol which combined with the polarization cost of

normalΔ G_{1, 3}^{0}

results in

ΔΔ G_{italicrx, 1}^{o} = 21.3 \pm 4.3

kJ/mol. Combining this value with the Boltzmann weight of this most representative conformation yields

ΔΔ G_{rx}^{o} = ΔΔ G_{italicrx, 1}^{o} + italicRT \ln ω_{1} = 20.2 \pm 4.3

kJ/mol according to Gill et al…”

Section: Resultsmentioning

confidence: 99%

Conformational sampling and polarization of Asp26 in pK_a calculations of thioredoxin

Gomez

Vöhringer‐Martinez

2019

Proteins

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“…The present method, which is available in the AMBER simulation package as of version 18,20 should be useful to accelerate calculations of thermodynamic averages in any setting where water equilibration is rate-limiting for pure MD simulations. We anticipate that it will be particularly valuable in calculating protein-ligand binding free energies where the binding site is isolated from bulk solvent, as it will allow water occupancy to change when a ligand is alchemically modified [44][45][46] or fully decoupled from the binding site. 6 It may also speed equilibration of protein conformation ensembles for proteins, such as BPTI, 47,48 which form cavities large enough to bind water in their folded state.…”

Section: Discussionmentioning

confidence: 99%

Simulating Water Exchange to Buried Binding Sites

Ben-Shalom¹,

Lin²,

Kurtman³

et al. 2018

Preprint

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Traditional molecular dynamics (MD) simulations of proteins, which rely on integration of Newton’s equations of motion, cannot efficiently equilibrate water occupancy for buried cavities in proteins. This leads to slow convergence of thermodynamic averages for such systems. We have addressed this challenge by efficiently integrating standard Metropolis Monte Carlo (MC) translational water moves with MD in the AMBER simulation package. The translational moves allow water to easily enter or exit buried sites in a thermodynamically correct way during a simulation. To maximize efficiency, the algorithm avoids moves that only interchange waters within the bulk around the protein, instead focusing on moves that can transfer water between bulk and the protein interior. In addition, a steric grid allows avoidance of moves that would lead to obvious steric clashes, and a fast grid-based energy evaluation is used to reduce the number of expensive full energy calculations. The potential energy distribution produced using MC/MD was found to be statistically indistinguishable from that of control simulations using only MD, and the algorithm effectively equilibrated water across steric barriers and into binding pockets that are not accessible with pure MD. The MC/MD method introduced here should be of increasing utility for applications spanning protein folding, the elucidation of protein mechanisms, and free energy calculations for computer-aided drug design. It is available in version 18 release of the widely disseminated AMBER simulation package.

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“…On the other hand, the efficiency of sampling strategies in the context of free energy calculations has been evaluated in many different ways in the past. In some cases, one or more system-specific collective variables associated with a slow degree of freedom can be directly inspected to verify thorough sampling [24,32,33]. This strategy requires extensive knowledge of the system and is not generally applicable to arbitrary receptor-ligand systems.…”

Section: We Need Robust General Strategies To Measure the Efficiency mentioning

confidence: 99%

The SAMPL6 SAMPLing challenge: Assessing the reliability and efficiency of binding free energy calculations

Rizzi

Jensen

Slochower

et al. 2019

Preprint

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Approaches for computing small molecule binding free energies based on molecular simulations are now regularly being employed by academic and industry practitioners to study receptor-ligand systems and prioritize the synthesis of small molecules for ligand design. Given the variety of methods and implementations available, it is natural to ask how the convergence rates and final predictions of these methods compare. In this study we describe the concept and results for the SAMPL6 SAMPLing challenge, the first challenge from the SAMPL series focusing on the assessment of convergence properties and reproducibility of binding free energy methodologies. We provided parameter files, partial charges, and multiple initial geometries for two octa-acid (OA) and one cucurbit[8]uril (CB8) host-guest systems. Participants submitted binding free energy predictions as a function of the number of force and energy evaluations for seven different alchemical and physical-pathway (i.e., potential of mean force and weighted ensemble of trajectories) methodologies implemented with the GROMACS, AMBER, NAMD, or OpenMM simulation engines. To rank the methods, we developed an efficiency statistic based on bias and variance of the free energy estimates. For the two small OA binders, the free energy estimates computed with alchemical and potential of mean force approaches show relatively similar variance and bias as a function of the number of energy/force evaluations, with the attach-pull-release (APR), GROMACS expanded ensemble, and NAMD double decoupling submissions obtaining the greatest efficiency. The differences between the methods increase when analyzing the CB8-quinine system, where both the guest size and correlation 1 of 43 Preprint ahead of submission -October 5, 2019times for system dynamics are greater. For this system, nonequilibrium switching (GROMACS/NS-DS/SB) obtained the overall highest efficiency. Surprisingly, the results suggest that specifying force field parameters and partial charges is insufficient to generally ensure reproducibility, and we observe differences between seemingly converged predictions ranging approximately from 0.3 to 1.0 kcal/mol, even with almost identical simulations parameters and system setup (e.g., Lennard-Jones cutoff, ionic composition). Further work will be required to completely identify the exact source of these discrepancies. Among the conclusions emerging from the data, we found that Hamiltonian replica exchange-while displaying very small variance-can be affected by a slowly-decaying bias that depends on the initial population of the replicas, that bidirectional estimators are significantly more efficient than unidirectional estimators for nonequilibrium free energy calculations for systems considered, and that the Berendsen barostat introduces non-negligible artifacts in expanded ensemble simulations.

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Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes via Nonequilibrium Candidate Monte Carlo

Cited by 77 publications

References 107 publications

Conformational sampling and polarization of Asp26 in pK_a calculations of thioredoxin

Conformational sampling and polarization of Asp26 in pK_a calculations of thioredoxin

Simulating Water Exchange to Buried Binding Sites

The SAMPL6 SAMPLing challenge: Assessing the reliability and efficiency of binding free energy calculations

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Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes via Nonequilibrium Candidate Monte Carlo

Cited by 77 publications

References 107 publications

Conformational sampling and polarization of Asp26 in pKa calculations of thioredoxin

Conformational sampling and polarization of Asp26 in pKa calculations of thioredoxin

Simulating Water Exchange to Buried Binding Sites

The SAMPL6 SAMPLing challenge: Assessing the reliability and efficiency of binding free energy calculations

Contact Info

Product

Resources

About

Conformational sampling and polarization of Asp26 in pK_a calculations of thioredoxin

Conformational sampling and polarization of Asp26 in pK_a calculations of thioredoxin