Electrostatic Origin of the Red Solvatochromic Shift of DFHBDI in RNA Spinach

Alkylated green fluorescent protein chromophores: dynamics in the gas phase and in aqueous solution

Fluorescent labelling of macromolecular samples, including using the green fluorescent protein (GFP), has revolutionised the field of bioimaging. The ongoing development of fluorescent proteins require a detailed understanding of the photophysics of the biochromophore, and how chemical derivatisation influences the excited state dynamics. Here, we investigate the photophysical properties associated with the S1 state of three alkylated derivatives of the chromophore in GFP, in the gas phase using time-resolved photoelectron imaging, and in water using femtosecond fluorescence upconversion. The gas-phase lifetimes (1.6-10 ps), which are associated with the intrinsic (environment independent) dynamics, are substantially longer than the lifetimes in water (0.06-3 ps), attributed to stabilisation of both twisted intermediate structures and conical intersection seams in the condensed phase. In the gas phase, alkylation on the 3 and 5 positions of the phenyl ring slows the dynamics due to inertial effects, while a 'pre-twist' of the methine bridge through alkylation on the 2 and 6 positions significantly shortens the excited state lifetimes. Formation of a minor, long-lived (≫ 40 ps) excited state population in the gas phase is attributed to intersystem crossing to a triplet state, accessed because of a T1/S1 degeneracy in the so-called P-trap potential energy minimum associated with torsion of the single-bond in the bridging unit connecting to the phenoxide ring. A small amount of intersystem crossing is supported through TD-DFT molecular dynamics trajectories and MS-CASPT2 calculations. No such intersystem crossing occurs in water at T = 300 K or in ethanol at T ≈ 77 K, due to a significantly altered potential energy surface and P-trap geometry.

Prediction of Fluorophore Brightness in Designed Mini Fluorescence Activating Proteins

The de novo computational design of proteins with predefined three-dimensional structure is becoming much more routine due to advancements both in force fields and algorithms. However, creating designs with functions beyond folding is more challenging. In that regard, the recent design of small beta barrel proteins that activate the fluorescence of an exogenous small molecule chromophore (DFHBI) is noteworthy. These proteins, termed mini fluorescence activating proteins (mFAPs), have been shown to increase the brightness of the chromophore more than 100-fold upon binding to the designed ligand pocket. The design process created a large library of variants with different brightness levels but gave no rational explanation for why one variant was brighter than another. Here, we use quantum mechanics and molecular dynamics simulations to investigate how molecular flexibility in the ground and excited states influences brightness. We show that the ability of the protein to resist dihedral angle rotation of the chromophore is critical for predicting brightness. Our simulations suggest that the mFAP/DFHBI complex has a rough energy landscape, requiring extensive ground-state sampling to achieve converged predictions of excited-state kinetics. While computationally demanding, this roughness suggests that mFAP protein function can be enhanced by reshaping the energy landscape toward conformations that better resist DFHBI bond rotation.

Data-driven modeling of S0 → S1 excitation energy in the BODIPY chemical space: High-throughput computation, quantum machine learning, and inverse design

Derivatives of BODIPY are popular fluorophores due to their synthetic feasibility, structural rigidity, high quantum yield, and tunable spectroscopic properties. While the characteristic absorption maximum of BODIPY is at 2.5 eV, combinations of functional groups and substitution sites can shift the peak position by ±1 eV. Time-dependent long-range corrected hybrid density functional methods can model the lowest excitation energies offering a semi-quantitative precision of ±0.3 eV. Alas, the chemical space of BODIPYs stemming from combinatorial introduction of-even a few dozen-substituents is too large for brute-force high-throughput modeling. To navigate this vast space, we select 77 412 molecules and train a kernel-based quantum machine learning model providing <2% hold-out error. Further reuse of the results presented here to navigate the entire BODIPY universe comprising over 253 giga (253 × 10⁹) molecules is demonstrated by inverse-designing candidates with desired target excitation energies.

Support Vector Regression-Based Monte Carlo Simulation of Flexible Water Clusters

Molecular simulations based on classical force fields are computationally efficient but lack accuracy due to the empirical formulation of non-bonded interactions. Quantum mechanical (QM) methods, albeit accurate, have inhibitory computational costs for large molecules and clusters. Hence, to overcome the bottleneck, machine learning (ML)-based methods have been employed in the recent years. We had earlier reported a combined scheme of many-body expansion (MBE) and ML to predict the interaction energies of rigid water clusters. In this work, we proceed toward building a flexible water model using the ML-MBE scheme. This ML-MBE scheme has an error of <1% for interaction energy prediction in comparison to the parent QM method for flexible water decamers. Machine learning-based Monte Carlo simulations (MLMC) are performed with this water model, and the structural properties of these configurations are compared with those obtained from ab initio molecular dynamics (AIMD) and the TIP3P classical force field. The radial distribution functions, tetrahedral order parameters, and number of hydrogen bonds in AIMD and MLMC have a similar qualitative and quantitative trend, whereas the classical force fields show a significant deviation.

A Multicolor Large Stokes Shift Fluorogen-Activating RNA Aptamer with Cationic Chromophores

Large Stokes shift (LSS) fluorescent proteins (FPs) exploit excited state proton transfer pathways to enable fluorescence emission from the phenolate intermediate of their internal 4-hydroxybenzylidene imidazolone (HBI) chromophore. An RNA aptamer named Chili mimics LSS FPs by inducing highly Stokes-shifted emission from several new green and red HBI analogues that are non-fluorescent when free in solution. The ligands are bound by the RNA in their protonated phenol form and feature a cationic aromatic side chain for increased RNA affinity and reduced magnesium dependence. In combination with oxidative functionalization at the C2 position of the imidazolone, this strategy yielded DMHBO⁺ , which binds to the Chili aptamer with a low-nanomolar K_D . Because of its highly red-shifted fluorescence emission at 592 nm, the Chili-DMHBO⁺ complex is an ideal fluorescence donor for Förster resonance energy transfer (FRET) to the rhodamine dye Atto 590 and will therefore find applications in FRET-based analytical RNA systems.

Unveiling Structural Motions of a Highly Fluorescent Superphotoacid by Locking and Fluorinating the GFP Chromophore in Solution

Superphotoacidity involves ultrafast proton motions implicated in numerous chemical and biological processes. We used conformational locking and strategic addition of electron-withdrawing substituents to synthesize a new GFP chromophore analogue: p-HO-3,5-diF-BDI:BF₂ (diF). It is highly fluorescent and exhibits excited-state proton transfer (ESPT) in various solvents, placing it among the strongest photoacids. Tunable femtosecond stimulated Raman spectroscopy with unique resonance conditions and transient absorption are complementarily employed to elucidate the structural basis for superphotoacidity. We reveal a multistep ESPT reaction from diF to methanol with an initial proton dissociation on the ∼600 fs time scale that forms a charge-separated state, stabilized by solvation, and followed by a diffusion-controlled proton transfer on the ∼350 ps time scale. A ∼1580 cm^-1 phenolic ring motion is uncovered to accompany ESPT before 1 ps. This study provides a vivid movie of the photoinduced proton dissociation of a superphotoacid with bright fluorescence, effectively bridging fundamental mechanistic insights to precise control of macroscopic functions.

Improving the Design of the Triple-Decker Motif in Red Fluorescent Proteins

We characterize computationally a red fluorescent protein (RFP) with the chromophore (Chro) sandwiched between two aromatic tyrosine rings in a triple-decker motif. According to the original proposal [ J. Phys. Chem. Lett. 2013 , 4 , 1743 ], such a tyrosine-chromophore-tyrosine π-stacked construct can be accommodated in the green fluorescent protein (GFP). A recent study [ ACS Chem. Biol. 2016 , 11 , 508 ] attempted to realize the triple-decker motif and obtained an RFP variant called mRojoA-VYGV with two tyrosine residues surrounding the chromophore. The crystal structure showed that only a tyrosine-chromophore pair was involved in π-stacking, whereas the second tyrosine was oriented perpendicularly, edge-to-face with respect to the chromophore. We propose a more promising variant of this RFP with a perfect triple-decker unit achieved by introducing additional mutations in mRojoA-VYGV. The structures and optical properties of model proteins based on the structures of mCherry and mRojoA are characterized computationally by QM(DFT)/MM. The electronic transitions in the protein-bound chromophores are computed by high-level quantum chemical methods. According to our calculations, the triple-decker chromophore unit in the new RFP variant is stable within the protein and its optical bands are red-shifted with respect to the parent mCherry and mRojoA species.