Retinal chromophore charge delocalization and confinement explain the extreme photophysics of Neorhodopsin

The understanding of how the rhodopsin sequence can be modified to exactly modulate the spectroscopic properties of its retinal chromophore, is a prerequisite for the rational design of more effective optogenetic tools. One key problem is that of establishing the rules to be satisfied for achieving highly fluorescent rhodopsins with a near infrared absorption. In the present paper we use multi-configurational quantum chemistry to construct a computer model of a recently discovered natural rhodopsin, Neorhodopsin, displaying exactly such properties. We show that the model, that successfully replicates the relevant experimental observables, unveils a geometrical and electronic structure of the chromophore featuring a highly diffuse charge distribution along its conjugated chain. The same model reveals that a charge confinement process occurring along the chromophore excited state isomerization coordinate, is the primary cause of the observed fluorescence enhancement

Computational studies of the mechanism of fluorescence enhancement and spectral tuning in arch neuronal optogenetic reporters

Several biological systems have evolved structures that can interact with light and exploit the photons energy for their biological functions. In fact, thanks to specialized organic molecules spread across all life kingdoms, life forms use light to trigger and regulate an incredible variety of different activities, including vision, photosynthesis, circadian rhythm, bioluminescence and in general a wide spectrum of biochemical processes. The common thread to all these activities is that they are invariably initiated by a photochemical reaction. Among these specialized structures, rhodopsins, membrane proteins harbouring a covalently bound retinal chromophore, play a preeminent role. In fact, while the first member of the rhodopsin family identified in the 1930s was the visual pigment of the animal retina, it was then found that this class of light-triggered proteins populates the whole spectrum of living organisms, where it promotes an astounding variety of biochemical processes, ranging from vision to cellular metabolism and sensorial function. More recently, rhodopsin became especially important in Optogenetics, a collection of neurobiology techniques where photo-sensitive proteins are used to control and visualize neural activity. The imaging of networks of interacting neurons is a particularly challenging task, since common fluorescence microscopy techniques require bright fluorescent probes localized in the neuron membrane. Ideally, such probes would also display a red-shifted maximum absorption wavelength, allowing to use excitation lasers with higher tissue penetration and reduced phototoxicity. Since rhodopsins are light-responsive membrane proteins, they are ideal candidates to report on action potentials. Archaerhodopsin-3 (Arch3) a microbial rhodopsin from Halorubrum Sodomense, was the first proposed rhodopsin-based fluorescent reporter. However, Arch3 has a fluorescence quantum yield (FQY) of ca. ~0.0001, which impairs the possibility to efficiently visualize the activity of neuronal populations. Throughout the years, several experiments of random and site-directed mutagenesis on Arch3 culminated in the discovery of variants with increased FQY, such as the Archers, the Archons, Arch5 and Arch7. These variants feature a brighter fluorescence enabling applications in imaging of acute brain slices, but also in living mammals and invertebrates. However, the FQY value are still in the range 0.001-0.01 and therefore not yet as bright as desirable. Therefore, it would be highly beneficial to develop computational tools for the high-throughput rational-design of rhodopsins with desired photochemical and/or photophysical properties. In my thesis, we provide the necessary theoretical foundations to envision the development of such tools. By constructing multiconfigurational quantum chemistry (MCQC) model of Arch3 and six of is variants, we establish a theory connecting the amino acid sequence to the increase of fluorescent brightness. We show that the observed experimental FQY trend correlates with the decrease in energy difference between the planar fluorescent emitting state and a newly characterized exotic diradical intermediate intercepted by a nearby photoisomerization channel. Investigating the molecular-level factors modulating this critical quantity, we show that the electronic structure of the retinal chromophore at the two minima is substantially different and that this is reflected by their different charge distributions. This is important because it indicates that a variation in the protein electrostatic potential that simultaneously stabilize the fluorescent state and destabilize the region of the decay channel would dramatically increase the FQY, suggesting an ideal target for microbial rhodopsins fluorescence engineering. Since all the reported Arch3 variants with increased FQY display also red-shifted absorption maximum, another appealing feature in Optogenetics, we used Arch3 as template to develop a new computational tool which allowed us to identify the critical opsin electrostatic variations that contribute to the spectral tuning. By designing an optimization procedure based on a variational protocol, we show that the “effective delocalization” of the counterion is the critical determinant of Arch3 absorption maximum. This theoretical framework agrees with the experimental findings, which heuristically identified in the counterion complex the most sensible replacements necessary to shift to the red the absorption of Arch3. Finally, using the same tool, we show that, in this family of rhodopsins, there is indeed a first-order relationship between maximum absorption wavelength and FQY

Molecular geometry impact on deep learning predictions of inverted singlet–triplet gaps

We present a deep learning model able to predict excited singlet-triplet gaps with a mean absolute error (MAE) of approximate to 20 meV to obtain potential inverted singlet-triplet (IST) candidates. We exploit cutting-edge spherical message passing graph neural networks designed specifically for generating 3D graph representations in molecular learning. In a nutshell, the model takes as input a list of unsaturated heavy atom Cartesian coordinates and atomic numbers, producing singlet-triplet gaps as output. We exploited available large data collections to train the model on approximate to 40,000 heterogeneous density functional theory (DFT) geometries with available ADC(2)/cc-pVDZ singlet-triplet gaps. We ascertain the predictive power of the model from a quantitative perspective obtaining predictions on a test set of approximate to 14,000 molecules, whose geometries have been generated at DFT level (the same employed for the geometries in the training set), at GFN2-xTB level, and through Molecular Mechanics. We notice performance degradation upon switching to lower-quality geometries, with GFN2-xTB ones maintaining satisfactory results (MAE approximate to 50 meV on GFN2-xTB geometries, MAE approximate to 180 meV on generalized AMBER force field geometries), hinting at caution when dealing with specific chemical classes. Finally, we verify the performance of the model from the qualitative point of view, obtaining predictions on a different data set of approximate to 15,000 molecules already used to identify new IST molecules. We obtained predictions using both DFT and experimental X-ray geometries, with results on IST candidates similar to those provided by quantum chemical methods, with clear hints for the path toward improved performance

Molecular Geometry Impact on Deep Learning Predictions of Inverted Singlet–Triplet Gaps

We present a deep learning model able to predict excited singlet–triplet gaps with a mean absolute error (MAE) of ≈20 meV to obtain potential inverted singlet–triplet (IST) candidates. We exploit cutting-edge spherical message passing graph neural networks designed specifically for generating 3D graph representations in molecular learning. In a nutshell, the model takes as input a list of unsaturated heavy atom Cartesian coordinates and atomic numbers, producing singlet–triplet gaps as output. We exploited available large data collections to train the model on ≈40,000 heterogeneous density functional theory (DFT) geometries with available ADC(2)/cc-pVDZ singlet–triplet gaps. We ascertain the predictive power of the model from a quantitative perspective obtaining predictions on a test set of ≈14,000 molecules, whose geometries have been generated at DFT level (the same employed for the geometries in the training set), at GFN2-xTB level, and through Molecular Mechanics. We notice performance degradation upon switching to lower-quality geometries, with GFN2-xTB ones maintaining satisfactory results (MAE ≈ 50 meV on GFN2-xTB geometries, MAE ≈ 180 meV on generalized AMBER force field geometries), hinting at caution when dealing with specific chemical classes. Finally, we verify the performance of the model from the qualitative point of view, obtaining predictions on a different data set of ≈15,000 molecules already used to identify new IST molecules. We obtained predictions using both DFT and experimental X-ray geometries, with results on IST candidates similar to those provided by quantum chemical methods, with clear hints for the path toward improved performance

Picosecond quantum-classical dynamics reveals that the coexistence of light-induced microbial and animal chromophore rotary motion modulates the isomerization quantum yield of heliorhodopsin

Rhodopsins are light-responsive proteins forming two vast and evolutionary distinct superfamilies whose functions are invariably triggered by the photoisomerization of a single retinal chromophore. In 2018 a third widespread superfamily of rhodopsins called heliorhodopsins was discovered using functional metagenomics. Heliorhodopsins, with their markedly different structural features with respect to the animal and microbial superfamilies, offer an opportunity to study how evolution has manipulated the chromophore photoisomerization to achieve adaptation. One question is related to the mechanism of such a reaction and how it differs from that of animal and microbial rhodopsins. To address this question, we use hundreds of quantum-classical trajectories to simulate the spectroscopically documented picosecond light-induced dynamics of a heliorhodopsin from the archaea thermoplasmatales archaeon (TaHeR). We show that, consistently with the observations, the trajectories reveal two excited state decay channels. However, inconsistently with previous hypotheses, only one channel is associated with the -C13C14- rotation of microbial rhodopsins while the second channel is characterized by the -C11C12- rotation typical of animal rhodopsins. The fact that such -C11C12- rotation is aborted upon decay and ground state relaxation, explains why illumination of TaHeR only produces the 13-cis isomer with a low quantum efficiency. We argue that the documented lack of regioselectivity in double-bond excited state twisting motion is the result of an "adaptation" that could be completely lost via specific residue substitutions modulating the steric hindrance experienced along the isomerization motion

Assessment of the Electron Correlation Treatment on the Quantum-Classical Dynamics of Retinal Protonated Schiff Base Models: XMS-CASPT2, RMS-CASPT2, and REKS Methods

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Evolution of the Automatic Rhodopsin Modeling (ARM) Protocol

5siIn recent years, photoactive proteins such as rhodopsins have become a common target for cutting-edge research in the field of optogenetics. Alongside wet-lab research, computational methods are also developing rapidly to provide the necessary tools to analyze and rationalize experimental results and, most of all, drive the design of novel systems. The Automatic Rhodopsin Modeling (ARM) protocol is focused on providing exactly the necessary computational tools to study rhodopsins, those being either natural or resulting from mutations. The code has evolved along the years to finally provide results that are reproducible by any user, accurate and reliable so as to replicate experimental trends. Furthermore, the code is efficient in terms of necessary computing resources and time, and scalable in terms of both number of concurrent calculations as well as features. In this review, we will show how the code underlying ARM achieved each of these properties.noneopenPedraza-González, Laura; Barneschi, Leonardo; Padula, Daniele; De Vico, Luca; Olivucci, MassimoPedraza-González, Laura; Barneschi, Leonardo; Padula, Daniele; De Vico, Luca; Olivucci, Massim

Pro219 is an electrostatic color determinant in the light-driven sodium pump KR2

Color tuning in animal and microbial rhodopsins has attracted the interest of many researchers, as the color of their common retinal chromophores is modulated by the amino acid residues forming the chromophore cavity. Critical cavity amino acid residues are often called “color switches”, as the rhodopsin color is effectively tuned through their substitution. Well-known color switches are the L/Q and A/TS switches located in the C and G helices of the microbial rhodopsin structure respectively. Recently, we reported on a third G/P switch located in the F helix of the light-driven sodium pumps of KR2 and JsNaR causing substantial spectral red-shifts in the latter with respect to the former. In order to investigate the molecular-level mechanism driving such switching function, here we present an exhaustive mutation, spectroscopic and computational investigation of the P219X mutant set of KR2. To do so, we study the changes in the absorption band of the 19 possible mutants and construct, semi-automatically, the corresponding hybrid quantum mechanics/molecular mechanics models. We found that the P219X feature a red-shifted light absorption with the only exception of P219R. The analysis of the corresponding models indicate that the G/P switch induces red-shifting variations via electrostatic interactions, while replacement-induced chromophore geometrical (steric) distortions play a minor role. However, the same analysis indicates that the P219R blue-shifted variant has a more complex origin involving both electrostatic and steric changes accompanied by protonation state and hydrogen bond networks modifications. These results make it difficult to extract simple rules or formulate theories for predicting how a switch operates without considering the atomistic details and environmental consequences of the side chain replacement

Automated QM/MM Screening of Rhodopsin Variants with Enhanced Fluorescence

We present a computational protocol for the fast and automated screening of excited-state hybrid quantum mechanics/molecular mechanics (QM/MM) models of rhodopsins to be used as fluorescent probes based on the automatic rhodopsin modeling protocol (a-ARM). Such "a-ARM fluorescence screening protocol" is implemented through a general Python-based driver, PyARM, that is also proposed here. The implementation and performance of the protocol are benchmarked using different sets of rhodopsin variants whose absorption and, more relevantly, emission spectra have been experimentally measured. We show that, despite important limitations that make unsafe to use it as a black-box tool, the protocol reproduces the observed trends in fluorescence and it is capable of selecting novel potentially fluorescent rhodopsins. We also show that the protocol can be used in mechanistic investigations to discern fluorescence enhancement effects associated with a near degeneracy of the S1/S2 states or, alternatively, with a barrier generated via coupling of the S0/S1 wave functions

On the fluorescence enhancement of arch neuronal optogenetic reporters

International audienceThe lack of a theory capable of connecting the amino acid sequence of a lightabsorbing protein with its fluorescence brightness is hampering the development of tools for understanding neuronal communications. Here we demonstrate that a theory can be established by constructing quantum chemical models of a set of Archaerhodopsin reporters in their electronically excited state. We found that the experimentally observed increase in fluorescence quantum yield is proportional to the computed decrease in energy difference between the fluorescent state and a nearby photoisomerization channel leading to an exotic diradical of the protein chromophore. This finding will ultimately support the development of technologies for searching novel fluorescent rhodopsin variants and unveil electrostatic changes that make light emission brighter and brighter