Modeling Spectral Tuning in Red Fluorescent Proteins Using the Dipole Moment Variation upon Excitation.

We describe a model for spectral tuning in red fluorescent proteins (RFPs) based on the relation between an electronic structure descriptor, the dipole moment variation upon excitation (DMV), and the excitation energy of a protein. This approach aims to overcome the problem of accurate prediction of excitation energies in RFPs, which span a very narrow window of band maxima. The latter roughly corresponds to the energy range of 0.1 eV, which is comparable with typical errors in calculations of the excitation energy by conventional quantum chemistry methods. In this work, we demonstrate a strong quantitative correlation between DMV values, obtained computationally with modest efforts, and excitation energies ΔEex at the experimental excitation band maxima for a series of RFPs with bands between 570 and 605 nm. Protein models are constructed by motifs of the relevant crystal structures, and atomic coordinates are optimized in quantum mechanics/molecular mechanics (QM/MM) calculations with QM-subsystems composed of large chromophore-containing regions. DMV values are evaluated with the electron density computed at the time-dependent density functional theory (TDDFT) level using several functionals and basis sets. We show that the results obtained with the CAM-B3LYP, BHHLYP, and M06-2X functionals demonstrate favorable correlations between DMV and ΔEex with the mean absolute error less than 0.01 eV. Taking into account the solid theoretical grounds of the relation between the DMV and the excitation energy in fluorescent proteins, the described modeling strategy presents a rational tool for spectral tuning in these efficient markers for in vivo imaging.

Mechanism of Guanosine Triphosphate Hydrolysis by the Visual Proteins Arl3-RP2: Free Energy Reaction Profiles Computed with Ab Initio Type QM/MM Potentials.

We report the results of calculations of the Gibbs energy profiles of the guanosine triphosphate (GTP) hydrolysis by the Arl3-RP2 protein complex using molecular dynamics (MD) simulations with ab initio type QM/MM potentials. The chemical reaction of GTP hydrolysis to guanosine diphosphate (GDP) and inorganic phosphate (Pi) is catalyzed by GTPases, the enzymes, which are responsible for signal transduction in live cells. A small GTPase Arl3, catalyzing the GTP → GDP reaction in complex with the activating protein RP2, constitute an essential part of the human vision cycle. To simulate the reaction mechanism, a model system is constructed by motifs of the crystal structure of the Arl3-RP2 complexed with a substrate analog. After selection of reaction coordinates, energy profiles for elementary steps along the reaction pathway GTP + H2O → GDP + Pi are computed using the umbrella sampling and umbrella integration procedures. QM/MM MD calculations are carried out, interfacing the molecular dynamics program NAMD and the quantum chemistry program TeraChem. Ab initio type QM(DFT)/MM potentials are computed with atom-centered basis sets 6-31G** and two hybrid functionals (PBE0-D3 and ωB97x-D3) of the density functional theory, describing a large QM subsystem. Results of these simulations of the reaction mechanism are compared to those obtained with QM/MM calculations on the potential energy surface using a similar description of the QM part. We find that both approaches, QM/MM and QM/MM MD, support the mechanism of GTP hydrolysis by GTPases, according to which the catalytic glutamine side chain (Gln71, in this system) actively participates in the reaction. Both approaches distinguish two parts of the reaction: the cleavage of the phosphorus-oxygen bond in GTP coupled with the formation of Pi, and the enzyme regeneration. Newly performed QM/MM MD simulations confirmed the profile predicted in the QM/MM minimum energy calculations, called here the pathway-I, and corrected its relief at the first elementary step from the enzyme-substrate complex. The QM/MM MD simulations also revealed another mechanism at the part of enzyme regeneration leading to pathway-II. Pathway-II is more consistent with the experimental kinetic data of the wild-type complex Arl3-RP2, whereas pathway-I explains the role of the mutation Glu138Gly in RP2 slowing down the hydrolysis rate.

Dipole Moment Variation Clears Up Electronic Excitations in the π-Stacked Complexes of Fluorescent Protein Chromophores.

We propose a quantitative structure-property relationship (QSPR) model for prediction of spectral tuning in cyan, green, orange, and red fluorescent proteins, which are engineered by motifs of the green fluorescent protein. Protein variants, in which their chromophores are involved in the π-stacking interaction with amino acid residues tyrosine, phenylalanine, and histidine, are prospective markers useful in bioimaging and super-resolution microscopy. In this work, we constructed training sets of the π-stacked complexes of four fluorescent protein chromophores (of the green, orange, red, and cyan series) with various substituted benzenes and imidazoles and tested the use of dipole moment variation upon excitation (DMV) as a descriptor to evaluate the vertical excitation energies in these systems. To validate this approach, we computed and analyzed electron density distributions of the π-stacked complexes and correlated the QSPR predictions with the reference values of the transition energies obtained using the high-level ab initio quantum chemistry methods. According to our results, the use of the DMV descriptor allows one to predict excitation energies in the π-stacked complexes with errors not exceeding 0.1 eV, which makes this model a practically useful tool in the development of efficient fluorescent markers for in vivo imaging.