A novel bioresponsive self-immolative spacer based on aza-quinone methide reactivity for the controlled release of thiols, phenols, amines, sulfonamides or amides.

A stimuli-sensitive linker is one of the indispensable components of prodrugs for cancer therapy as it covalently binds the drug and releases it upon external stimulation at the tumour site. Quinone methide elimination has been widely used as the key transformation to release drugs based on their nucleofugacity. The usual approach is to bind the drug to the linker as a carbamate and release it as a free amine after a self-immolative 1,6-elimination. Although this approach is very efficient, it is limited to amines (as carbamates), alcohols or phenols (as carbonates) or other acidic functional groups. We report here a self-immolative spacer capable of directly linking and releasing amines, phenols, thiols, sulfonamides and carboxyamides after a reductive stimulus. The spacer is based on the structure of (5-nitro-2-pyrrolyl)methanol (NPYM-OH), which was used for the direct alkylation of the functional groups mentioned above. The spacer is metabolically stable and has three indispensable sites for bioconjugation: the bioresponsive trigger, the conjugated 1,6 self-immolative system and a third arm suitable for conjugation with a carrier or other modifiers. Release was achieved by selective reduction of the nitro group over Fe/Pd nanoparticles (NPs) in a micellar aqueous environment (H2O/TPGS-750-M), or by NADH mediated nitroreductase activation. A DFT study demonstrates that, during the 1,6 elimination, the transition state formed from 5-aminopyrrole has a lower activation energy compared to other 5-membered heterocycles or p-aminobenzyl derivatives. The NPYM scaffold was validated by late-stage functionalisation of approved drugs such as celecoxib, colchicine, vorinostat or ciprofloxacin. A hypoxia-activated NPYM-based prodrug (HAP) derived from HDAC inhibitor ST7612AA1 was also produced, which was active in cancer cells under hypoxic conditions.

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.

Formation of electron traps in semiconducting polymers via a slow triple-encounter between trap precursor particles.

Already in 2012, Blom et al. reported (Nature Materials 2012, 11, 882) in semiconducting polymers on a general electron-trap density of ≈3 × 1017 cm-3, centered at an energy of ≈3.6 eV below vacuum. It was suggested that traps have an extrinsic origin, with the water-oxygen complex [2(H2O)-O2] as a possible candidate, based on its electron affinity. However, further evidence is lacking and the origin of universal electron traps remained elusive. Here, in polymer diodes, the temperature-dependence of reversible electron traps is investigated that develop under bias stress slowly over minutes to a density of 2 × 1017 cm-3, centered at an energy of 3.6 eV below vacuum. The trap build-up dynamics follows a 3rd-order kinetics, in line with that traps form via an encounter between three diffusing precursor particles. The accordance between universal and slowly evolving traps suggests that general electron traps in semiconducting polymers form via a triple-encounter process between oxygen and water molecules that form the suggested [2(H2O)-O2] complex as the trap origin.

Formation of universal electron traps in polymer light-emitting diodes is a dynamic process that occurs via a slow triple-encounter between trap precursor species, with the water-oxygen [2(H₂O)-O₂] complex as a likely candidate.

A Computational Perspective on the Reactivity of π-spacers in Self-Immolative Elimination Reactions.

The controlled release of chemicals, especially in drug delivery, is crucial, often employing "self-immolative" spacers to enhance reliability. These spacers separate the payload from the protecting group, ensuring a more controlled release. Over the years, design rules have been proposed to improve the elimination process's reaction rate by modifying spacers with electron-donating groups or reducing their aromaticity. The spacer design is critical for determining the range of functional groups released during this process. This study explores various strategies from the literature aimed at improving release rates, focusing on the electronic nature of the spacer, its aromaticity, the electronic nature of its substituents, and the leaving groups involved in the elimination reaction. Through computational analysis, I investigate activation free energies by identifying transition states for model reactions. My calculations align qualitatively with experimental results, demonstrating the feasibility and reliability of computationally pre-screening model self-immolative eliminations. This approach allows proposing optimal combinations of spacer and leaving group for achieving the highest possible release rate.

Identification of Unknown Inverted Singlet-Triplet Cores by High-Throughput Virtual Screening.

Molecules where the energy of the lowest excited singlet state is found below the energy of the lowest triplet state (inverted singlet-triplet molecules) are extremely rare. It is particularly challenging to discover new ones through virtual screening because the required wavefunction-based methods are expensive and unsuitable for high-throughput calculations. Here, we devised a virtual screening approach where the molecules to be considered with advanced methods are pre-selected with increasingly more sophisticated filters that include the evaluation of the HOMO-LUMO exchange integral and approximate CASSCF calculations. A final set of 7 candidates (0.05% of the initial 15 000) were verified to possess inversion between singlet and triplet states with state-of-the-art multireference methods (MS-CASPT2). One of them is deemed of particular interest because it is unrelated to other proposals made in the literature.

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.

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.

Accurate Quantum-Mechanically Derived Force-Fields through a Fragment-Based Approach: Balancing Specificity and Transferability in the Prediction of Self-Assembly in Soft Matter.

The wide range of time/length scales covered by self-assembly in soft matter makes molecular dynamics (MD) the ideal candidate for simulating such a supramolecular phenomenon at an atomistic level. However, the reliability of MD outcomes heavily relies on the accuracy of the adopted force-field (FF). The spontaneous re-ordering in liquid crystalline materials stands as a clear example of such collective self-assembling processes, driven by a subtle and delicate balance between supramolecular interactions and single-molecule flexibility. General-purpose transferable FFs often dramatically fail to reproduce such complex phenomena, for example, the error on the transition temperatures being larger than 100 K. Conversely, quantum-mechanically derived force-fields (QMD-FFs), specifically tailored for the target system, were recently shown (J. Phys. Chem. Lett.2022,13, 243) to allow for the required accuracy as they not only well reproduced transition temperatures but also yielded a quantitative agreement with the experiment on a wealth of structural, dynamic, and thermodynamic properties. The main drawback of this strategy stands in the computational burden connected to the numerous quantum mechanical (QM) calculations usually required for a target-specific parameterization, which has undoubtedly hampered the routine application of QMD-FFs. In this work, we propose a fragment-based strategy to extend the applicability of QMD-FFs, in which the amount of QM calculations is significantly reduced, being a single-molecule-optimized geometry and its Hessian matrix the only QM information required. To validate this route, a new FF is assembled for a large mesogen, exploiting the parameters obtained for two smaller liquid crystalline molecules, in this and previous work. Lengthy MD simulations are carried out with the new transferred QMD-FF, observing again a spontaneous re-orientation in the correct range of temperatures, with good agreement with the available experimental measures. The present results strongly suggest that a partial transfer of QMD-FF parameters can be invoked without a significant loss of accuracy, thus paving the way to exploit the method's intrinsic predictive capabilities in the simulation of novel soft materials.

On the fluorescence enhancement of arch neuronal optogenetic reporters.

The lack of a theory capable of connecting the amino acid sequence of a light-absorbing 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.

Exciton transport in molecular organic semiconductors boosted by transient quantum delocalization.

Designing molecular materials with very large exciton diffusion lengths would remove some of the intrinsic limitations of present-day organic optoelectronic devices. Yet, the nature of excitons in these materials is still not sufficiently well understood. Here we present Frenkel exciton surface hopping, an efficient method to propagate excitons through truly nano-scale materials by solving the time-dependent Schrödinger equation coupled to nuclear motion. We find a clear correlation between diffusion constant and quantum delocalization of the exciton. In materials featuring some of the highest diffusion lengths to date, e.g. the non-fullerene acceptor Y6, the exciton propagates via a transient delocalization mechanism, reminiscent to what was recently proposed for charge transport. Yet, the extent of delocalization is rather modest, even in Y6, and found to be limited by the relatively large exciton reorganization energy. On this basis we chart out a path for rationally improving exciton transport in organic optoelectronic materials.

Evolution of the Automatic Rhodopsin Modeling (ARM) Protocol.

In 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.

Organic materials repurposing, a data set for theoretical predictions of new applications for existing compounds.

We present a data set of 48182 organic semiconductors, constituted of molecules that were prepared with a documented synthetic pathway and are stable in solid state. We based our search on the Cambridge Structural Database, from which we selected semiconductors with a computational funnel procedure. For each entry we provide a set of electronic properties relevant for organic materials research, and the electronic wavefunction for further calculations and/or analyses. This data set has low bias because it was not built from a set of materials designed for organic electronics, and thus it provides an excellent starting point in the search of new applications for known materials, with a great potential for novel physical insight. The data set contains molecules used as benchmarks in many fields of organic materials research, allowing to test the reliability of computational screenings for the desired application, "rediscovering" well-known molecules. This is demonstrated by a series of different applications in the field of organic materials, confirming the potential for the repurposing of known organic molecules.

Bright Frenkel Excitons in Molecular Crystals: A Survey.

We computed the optical properties of a large set of molecular crystals (∼2200 structures) composed of molecules whose lowest excited states are strongly coupled and generate wide excitonic bands. Such bands are classified in terms of their dimensionality (1-, 2-, and 3-dimensional), the position of the optically allowed state in relation with the excitonic density of states, and the presence of Davydov splitting. The survey confirms that one-dimensional aggregates are rare in molecular crystals highlighting the need to go beyond the simple low-dimensional models. Furthermore, this large set of data is used to search for technologically interesting and less common properties. For instance, we considered the largest excitonic bandwidth that is achievable within known molecular crystals and identified materials with strong super-radiant states. Finally, we explored the possibility that strong excitonic coupling can be used to generate emissive states in the near-infrared region in materials formed by molecules with bright visible absorption and we could identify the maximum allowable red shift in this material class. These insights with the associated searchable database provide practical guidelines for designing materials with interesting optical properties.

Computational Identification of Novel Families of Nonfullerene Acceptors by Modification of Known Compounds.

We considered a database of tens of thousands of known organic semiconductors and identified those compounds with computed electronic properties (orbital energies, excited state energies, and oscillator strengths) that would make them suitable as nonfullerene electron acceptors in organic solar cells. The range of parameters for the desirable acceptors is determined from a set of experimentally characterized high-efficiency nonfullerene acceptors. This search leads to ∼30 lead compounds never considered before for organic photovoltaic applications. We then proceed to modify these compounds to bring their computed solubility in line with that of the best small-molecule nonfullerene acceptors. A further refinement of the search can be based on additional properties like the reorganization energy for chemical reduction. This simple strategy, which relies on a few easily computable parameters and can be expanded to a larger set of molecules, enables the identification of completely new chemical families to be explored experimentally.

Shortwave infrared-absorbing squaraine dyes for all-organic optical upconversion devices.

Shortwave infrared (SWIR) optical sensing and imaging are essential to an increasing number of next-generation applications in communications, process control or medical imaging. An all-organic SWIR upconversion device (OUC) consists of an organic SWIR sensitive photodetector (PD) and an organic light-emitting diode (OLED), connected in series. OUCs directly convert SWIR to visible photons, which potentially provides a low-cost alternative to the current inorganic compound-based SWIR imaging technology. For OUC applications, only few organic materials have been reported with peak absorption past 1000 nm and simultaneous small absorption in the visible. Here, we synthesized a series of thermally stable high-extinction coefficient donor-substituted benz[cd]indole-capped SWIR squaraine dyes. First, we coupled the phenyl-, carbazole-, and thienyl-substituted benz[cd]indoles with squaric acid (to obtain the SQ dye family). We then combined these donors with the dicyanomethylene-substituted squaraine acceptor unit, to obtain the dicyanomethylene-functionalized squaraine DCSQ family. In the solid state, the absorbance of all dyes extended considerably beyond 1100 nm. For the carbazole- and thienyl-substituted DCSQ dyes, even the peak absorptions in solution were in the SWIR, at 1008 nm and 1014 nm. We fabricated DCSQ PDs with an external photon-to-current efficiency over 30%. We then combined the PD with a fluorescent OLED and fabricated long-term stable OUCs with peak sensitivity at 1020 nm, extending to beyond 1200 nm. Our OUCs are characterized by a very low dark luminance (<10-2 cd m-2 at below 6 V) in the absence of SWIR light, and a low turn-on voltage of 2 V when SWIR light is present.

Amplification of the chiroptical response of UV-transparent amines and alcohols by N-phthalimide derivatization enabling absolute configuration determination through ECD computational analysis.

The stereoselective transformation of chiral UV-transparent amines and alcohols to phthalimides has proved to be a simple and efficient method to enhance the chiroptical response of these substrates allowing their reliable absolute configuration determination by computational analysis of ECD spectra. Such a transformation also leads to a significant reduction in the molecular conformational flexibility thus simplifying the conformational analysis required by the computational treatment. The method described herein thus allows the absolute configuration assignment to these challenging substrates to be much easier and reliable.

On the arrangement of chromophores in light harvesting complexes: chance versus design.

We used a homogeneous computational approach to derive the excitonic Hamiltonian for five light harvesting complexes containing only one type of chromophore and compare them in terms of statistical descriptors. We then studied the approximate exciton dynamics for the five complexes introducing a measure, the (averaged and time-dependent) inverse participation ratio, that enables the comparison between very diverse complexes on the same ground. We find that the global dynamics are very similar across the set of systems despite the variety of geometric structures of the complexes. In particular, the dynamics of four out of five light harvesting complexes are barely distinguishable with a small variation from the norm seen only for the Fenna-Matthews-Olson complex. We use the information from the realistic Hamiltonians to build a reduced model system that shows how the global dynamics are ultimately dominated by a single parameter, the degree of localization of the excitonic Hamiltonian eigenstates. Considering the physically plausible range of system parameters, the reduced model explains why the dynamics are so similar across most light harvesting complexes containing a single type of chromophore regardless of the detailed pattern of the inter-chromophore excitonic coupling.

How fine-tuned for energy transfer is the environmental noise produced by proteins around biological chromophores?

We investigate the role of the local protein environment on the energy transfer processes in biological molecules, excluding from the analysis the effect of intra-chromophore nuclear motions, and focussing on the exciton-phonon coupling. We studied three different proteins (FMO and two variants of the WSCP protein) with different biological functions but similar chromophores, to understand whether a classification of chromophores based on the details of the environment would be possible, and whether specific environments enhance or suppress the coupling between exciton and protein dynamics. Our results show that despite the different biological role, there is no significant difference in the influence of the environment on the properties of the chromophores. Additionally, we show that the main role in influencing molecular properties is played by solvent molecules: the interaction occurs on a medium-range scale, and the solvent is kept in place by a strong H-bond network being free to rotate, suggesting a dipole-dipole interaction mechanism. Steric hindrance exerted by other moieties can help modulating the interactions and tuning the energy transfer process. Overall, considering also the relatively greater importance of intra-molecular nuclear motions, the protein environment around biological chromophores does not appear fine-tuned for a specific function.

How and How Much Molecular Conformation Affects Electronic Circular Dichroism: The Case of 1,1-Diarylcarbinols.

Chiroptical spectra such as electronic circular dichroism (ECD) are said to be much more sensitive to conformation than their non-chiroptical counterparts, however, it is difficult to demonstrate such a common notion in a clear-cut way. We run DFT and TDDFT calculations on two closely related 1,1-diarylmethanols which show mirror-image ECD spectra for the same absolute configuration. We demonstrate that the main reason for the different chiroptical response of the two compounds lies in different conformational ensembles, caused by a single hydrogen-to-methyl substitution. We conclude that two compounds, having the same configuration but different conformation, may exhibit mirror-image ECD signals, stressing the importance and impact of conformational factors on ECD spectra.