title: Enhancing constant-pH simulation in explicit solvent with a two-dimensional replica exchange method.
abstract: We present a new method for enhanced sampling for constant-pH simulations in explicit water based on a two-dimensional (2D) replica exchange scheme. The new method is a significant extension of our previously developed constant-pH simulation method, which is based on enveloping distribution sampling (EDS) coupled with a one-dimensional (1D) Hamiltonian exchange method (HREM). EDS constructs a hybrid Hamiltonian from multiple discrete end state Hamiltonians that, in this case, represent different protonation states of the system. The ruggedness and heights of the hybrid Hamiltonian's energy barriers can be tuned by the smoothness parameter. Within the context of the 1D EDS-HREM method, exchanges are performed between replicas with different smoothness parameters, allowing frequent protonation-state transitions and sampling of conformations that are favored by the end-state Hamiltonians. In this work, the 1D method is extended to 2D with an additional dimension, external pH. Within the context of the 2D method (2D EDS-HREM), exchanges are performed on a lattice of Hamiltonians with different pH conditions and smoothness parameters. We demonstrate that both the 1D and 2D methods exactly reproduce the thermodynamic properties of the semigrand canonical (SGC) ensemble of a system at a given pH. We have tested our new 2D method on aspartic acid, glutamic acid, lysine, a four residue peptide (sequence KAAE), and snake cardiotoxin. In all cases, the 2D method converges faster and without loss of precision; the only limitation is a loss of flexibility in how CPU time is employed. The results for snake cardiotoxin demonstrate that the 2D method enhances protonation-state transitions, samples a wider conformational space with the same amount of computational resources, and converges significantly faster overall than the original 1D method.
authors.affiliation: Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health , Bethesda, Maryland 20892, United States.
authors.forename: Juyong
authors.initials: J
authors.lastname: Lee
authors.affiliation: Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health , Bethesda, Maryland 20892, United States.
authors.forename: Benjamin T
authors.initials: BT
authors.lastname: Miller
authors.affiliation: Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health , Bethesda, Maryland 20892, United States.|Department of Biophysics, Johns Hopkins University , Baltimore, Maryland 21218, United States.
authors.forename: Ana
authors.initials: A
authors.lastname: Damjanović
authors.affiliation: Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health , Bethesda, Maryland 20892, United States.
authors.forename: Bernard R
authors.initials: BR
authors.lastname: Brooks
mesh_terms: D000818:Animals; D001224:Aspartic Acid / Q000737:chemistry*; D054715:Cardiotoxins / Q000737:chemistry*; D018698:Glutamic Acid / Q000737:chemistry*; D006863:Hydrogen-Ion Concentration; D008239:Lysine / Q000737:chemistry*; D056004:Molecular Dynamics Simulation; D010455:Peptides / Q000737:chemistry*; D012911:Snakes; D012997:Solvents / Q000737:chemistry*; D013816:Thermodynamics
chemical_list: D054715:Cardiotoxins; D010455:Peptides; D012997:Solvents; D001224:Aspartic Acid; D018698:Glutamic Acid; D008239:Lysine