pH-Dependent Transient Conformational States Control Optical Properties in Cyan Fluorescent Protein

Abstract

A recently engineered mutant of cyan fluorescent protein (WasCFP) that exhibits pH-dependent absorption suggests that its tryptophan-based chromophore switches between neutral (protonated) and charged (deprotonated) states depending on external pH. At pH 8.1 the latter gives rise to green fluorescence as opposed to the cyan color of emission that is characteristic for the neutral form at low pH. Given the high energy cost of deprotonating the tryptophan at the indole nitrogen, this behavior is puzzling, even if the stabilizing effect of the V61K mutation in the proximity of the protonation/deprotonation site is considered. Due to its potential to open new avenues for the development of optical sensors and photoconvertible fluorescent proteins, a mechanistic understanding of how the charged state in WasCFP can possibly be stabilized is, thus, important. Attributed to the dynamic nature of proteins, such understanding often requires knowledge of the various conformations adopted, including transiently populated conformational states. Transient conformational states triggered by pH are of emerging interest, and have been shown to be important whenever ionizable groups interact with hydrophobic environments. Using a combination of the weighted-ensemble sampling method and explicit solvent constant pH molecular dynamics (CPHMDMSλD) simulations, we have identified a solvated transient state, characterized by a partially open β-barrel where the chromophore pKa of 6.8 is shifted by over 20 units from that in the closed form (6.8 and 31.7, respectively). This state contributes a small population at low pH (12% at pH 6.1), but becomes dominant at mildly basic conditions, contributing as much as 53% at pH 8.1. This pH-dependent population shift between neutral (at pH 6.1) and charged (at pH 8.1) forms is thus responsible for the observed absorption behavior of WasCFP. Our findings demonstrate the conditions necessary to stabilize the charged state of the WasCFP chromophore (namely, local solvation at the deprotonation site and a partial flexibility of the protein β-barrel structure) and provide the first evidence that transient conformational states can control optical properties of fluorescent proteins.

Mapping the Ligand Binding Landscape

“…A set of regions is defined in conformation space, and trajectories are cloned in under-represented regions (e.g., saddle points) and merged in over-represented regions (e.g., high-probability basins of attraction). The WE method has largely been implemented by defining these regions along one or two order parameters (22, 45, 46, 47), and the key advance of the WExplore method was to define regions in a high-dimensional-order parameter space using hierarchical Voronoi polyhedra (for more information, see (23)). We have found WExplore to be useful for discovering new regions of conformational space (48), and it works best for low-entropy to high-entropy transitions, such as ligand unbinding pathways (10, 24, 25, 27).…”

Mapping the ligand binding landscape

“…high probability basins of attraction). The weighted ensemble method has largely been implemented by defining these regions along one or two order parameters [22,[43][44][45], and the key advance of the WExplore method was to define regions in a high-dimensional order parameter space using hierarchical Voronoi polyhedra (for more information, see [23]). We have found WExplore to be useful for discovering new regions of conformational space [46], and it works best for low-entropy to high-entropy transitions, such as ligand unbinding pathways [10,24,25,47].…”

Multiple Ligand Unbinding Pathways and Ligand-Induced Destabilization Revealed by WExplore

“…Here we use our own technique, WExplore (17), to investigate a broad set of ligand release pathways in the trypsinbenzamidine system. This and related methods have been used to study protein unfolding, hydration changes near a fluorophore (18), long timescale conformational transitions in a RNA helix-helix junction (19), and to generate the ensemble of unbinding pathways of small ligands from the protein FKBP (20). Like MSM approaches, it uses trajectories that are run with the unbiased Hamiltonian and are suitable for a network-based conformation analysis (21)(22)(23), but it is based on a weighted ensemble of trajectories, and obtains unbinding rates by a different mechanism that does not rely on a Markovian assumption of transitions between regions.…”