title: Computational scheme for pH-dependent binding free energy calculation with explicit solvent.
abstract: We present a computational scheme to compute the pH-dependence of binding free energy with explicit solvent. Despite the importance of pH, the effect of pH has been generally neglected in binding free energy calculations because of a lack of accurate methods to model it. To address this limitation, we use a constant-pH methodology to obtain a true ensemble of multiple protonation states of a titratable system at a given pH and analyze the ensemble using the Bennett acceptance ratio (BAR) method. The constant pH method is based on the combination of enveloping distribution sampling (EDS) with the Hamiltonian replica exchange method (HREM), which yields an accurate semi-grand canonical ensemble of a titratable system. By considering the free energy change of constraining multiple protonation states to a single state or releasing a single protonation state to multiple states, the pH dependent binding free energy profile can be obtained. We perform benchmark simulations of a host-guest system: cucurbit[7]uril (CB[7]) and benzimidazole (BZ). BZ experiences a large pKa shift upon complex formation. The pH-dependent binding free energy profiles of the benchmark system are obtained with three different long-range interaction calculation schemes: a cutoff, the particle mesh Ewald (PME), and the isotropic periodic sum (IPS) method. Our scheme captures the pH-dependent behavior of binding free energy successfully. Absolute binding free energy values obtained with the PME and IPS methods are consistent, while cutoff method results are off by 2 kcal mol(-1) . We also discuss the characteristics of three long-range interaction calculation methods for constant-pH simulations.
authors.affiliation: Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, Maryland, 20892.
authors.forename: Juyong
authors.identifier: http://orcid.org/0000-0003-1174-4358
authors.initials: J
authors.lastname: Lee
authors.affiliation: Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, Maryland, 20892.
authors.forename: Benjamin T
authors.initials: BT
authors.lastname: Miller
authors.affiliation: Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, Maryland, 20892.
authors.forename: Bernard R
authors.initials: BR
authors.lastname: Brooks
mesh_terms: D001562:Benzimidazoles / Q000737:chemistry*; D001665:Binding Sites; D001952:Bridged-Ring Compounds / Q000737:chemistry*; D006863:Hydrogen-Ion Concentration; D007093:Imidazoles / Q000737:chemistry*; D056004:Molecular Dynamics Simulation; D012997:Solvents / Q000737:chemistry; D013816:Thermodynamics; D047028:Macrocyclic Compounds; D000099246:Cucurbit(n)urils
chemical_list: D001562:Benzimidazoles; D001952:Bridged-Ring Compounds; D007093:Imidazoles; D012997:Solvents; C456276:cucurbit(7)uril; D047028:Macrocyclic Compounds; D000099246:Cucurbit(n)urils; C031000:benzimidazole
keywords: Bennett acceptance ratio; EDS-HREM; absolute binding free energy calculation; binding affinity; constant-pH simulation; host-guest system; pH-dependence