The principal drawback is the computational cost that can be overcome by modification of the underlying model representation or implementation (e.g., the reintroduction of pseudo-parameters), or by improvements in computing power. Molecular dynamics simulations offer an attractive solution for sampling biomolecular ensembles spanning meaningfully long timescales with fully atomistic representations of both protein and solvent. These simulations and the resultant ensembles might be used as input for a PB-based approach , or can be performed in conjunction with a free energy method (e.g., thermodynamicintegration , free energy perturbation , etc.), allowing for a direct resolution of the ∆∆G between protonation states. An alternative MD-based approach is constant-pH molecular dynamics (CpHMD) simulations. Here, Monte Carlo sampling (discrete CpHMD) or λdynamics (continuous CpHMD) are used to explicitly sample protonation events. This allows for an explicit consideration of the proton concentration, where the protonation states of titratable residues are not restrained, but are allowed to dynamically follow the free energy gradient.