Attach-Pull-Release Calculations of Ligand Binding and Conformational Changes on the First BRD4 Bromodomain

Abstract

Bromodomains, protein domains involved in epigenetic regulation, are able to bind small molecules with high affinity. In the present study, we report free energy calculations for the binding of seven ligands to the first BRD4 bromodomain, using the attach-pull-release (APR) method to compute the reversible work of removing the ligands from the binding site and then allowing the protein to relax conformationally. We test three different water models, TIP3P, TIP4PEw, and SPC/E, as well as the GAFF and GAFF2 parameter sets for the ligands. Our simulations show that the apo crystal structure of BRD4 is only metastable, with a structural transition happening in the absence of the ligand typically after 20 ns of simulation. We compute the free energy change for this transition with a separate APR calculation on the free protein and include its contribution to the ligand binding free energies, which generally causes an underestimation of the affinities. By testing different water models and ligand parameters, we are also able to assess their influence in our results and determine which one produces the best agreement with the experimental data. Both free energies associated with the conformational change and ligand binding are affected by the choice of water model, with the two sets of ligand parameters affecting their binding free energies to a lesser degree. Across all six combinations of water model and ligand potential function, the Pearson correlation coefficients between calculated and experimental binding free energies range from 0.55 to 0.83, and the root-mean-square errors range from 1.4–3.2 kcal/mol. The current protocol also yields encouraging preliminary results when used to assess the relative stability of ligand poses generated by docking or other methods, as illustrated for two different ligands. Our method takes advantage of the high performance provided by graphics processing units and can readily be applied to other ligands as well as other protein systems.

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

“…However, in practice sampling transitions between binding modes using MD is typically inefficient because of large energy barriers (and hence slow timescales) separating binding modes. 1,20,31,32 …”

Automated docking refinement and virtual compound screening with absolute binding free energy calculations

“…This can be accomplished by a non-physical (i.e. alchemical) decoupling pathway, 15,16,25 in which the ligand is, in effect, decoupled from the binding site and recoupled with bulk solvent; or by modeling the physical process of moving the fully coupled ligand out of the binding site 18,[26][27][28] into solvent. It is worth noting that any valid ABFE method must account for the free energy of releasing the ligand to bulk solvent at standard concentration.…”

“…16 The RBFE and ABFE approaches have shown similar accuracy, relative to experiment, with computed binding free energies consistently showing root-mean-square deviations from experiment close to 1 kcal/mol. 9,12,19,25,27 Because ABFE calculations do not involve the alchemical conversion of one compound into another, they can be applied to more diverse sets of compounds, and therefore should be a better fit to the task of screening a library of diverse compounds for binding to a targeted protein. 12,20,25,27 However, this application is complicated by the fact that typical MD simulations are too short to allow a ligand initially modeled in one suggested pose to sample a variety of different poses.…”

“…9,12,19,25,27 Because ABFE calculations do not involve the alchemical conversion of one compound into another, they can be applied to more diverse sets of compounds, and therefore should be a better fit to the task of screening a library of diverse compounds for binding to a targeted protein. 12,20,25,27 However, this application is complicated by the fact that typical MD simulations are too short to allow a ligand initially modeled in one suggested pose to sample a variety of different poses. Because the chemical potential of the bound state is dominated by contributions from the most stable pose(s), this means it is essential that binding free energy calculations start from the most stable poses.…”

“…Encouragingly, several prior studies show that ABFE calculations may be used to determine the relative stability of various plausible binding modes of a given ligand. 19,20,27 Thus, we have the possibility of a workflow in which ABFE calculations are carried out for multiple plausible poses provided by a docking program, and the results are synthesized to provide information on which poses are most stable and on the overall binding free energy of the ligand. The present study is a step toward this goal.…”