Hole-hole Tamm-Dancoff-approximated density functional theory: A highly efficient electronic structure method incorporating dynamic and static correlation

Combining low-cost electronic structure theory and low-cost parallel computing architecture

The computational efficiency of low-cost electronic structure methods can be further improved by leveraging heterogenous computing architectures. The software package TeraChem has been developed since 2008 to make use of graphical processing units (GPUs), particularly their strong single-precision performance, for the acceleration of quantum chemical calculations. Here, we present the implementation of three low-cost methods, namely HF-3c, PBEh-3c, and the recently introduced ωB97X-3c. We show that these can benefit in terms of performance when combined with "consumer grade" GPUs by leveraging the mixed precision integral handling in TeraChem. The current limitation of the latter's GPU integral library is that Gaussian integrals only for functions with angular momentum l < 3 can be computed, which generally restricts the achievable accuracy in terms of the one-particle basis set. Particularly, the implementation of the ωB97X-3c method now enables higher accuracy with this setting which, in turn, provides the most efficient implementation accessible with consumer-grade hardware. We furthermore show that the implemented 3c methods can be combined with the hh-TDA formalism. This gives new and efficient low-cost multi-configurational excited states methods, which are benchmarked for the description of lowest vertical excitation energies in this work. All in all, the combination of these efficient electronic structure theory methods with affordable highly parallelized computing hardware provides an optimal computational and monetary cost to accuracy ratio.

Development of Parallel On-the-Fly Algorithm for Global Exploration of Conical Intersection Seam Space

Conical intersection (CI) seams are configuration spaces of a molecular system where two or more (spin) adiabatic electronic states are degenerate in energy. They play essential roles in photochemistry because nonradiative decays often occur near the minima of the seam, i.e., the minimum energy CIs (MECIs). Thus, it is important to explore the CI seams and discover the MECIs. Although various approaches exist for CI seam exploration, most of them are local in nature, requiring reasonable initial guesses of geometries and nuclear gradients during the search. Global search algorithms, on the other hand, are powerful because they can fully sample the configurational space and locate important MECIs missed by local algorithms. However, global algorithms are often computationally expensive for large systems due to their poor scalability with respect to the number of degrees of freedom. To overcome this challenge, we develop the parallel on-the-fly Crystal algorithm to globally explore the CI seam space, taking advantage of its superior scaling behavior. Specifically, Crystal is coupled with on-the-fly evaluations of the excited and ground state energies using multireference electronic structure methods. Meanwhile, the algorithm is parallelized to further boost its computational efficiency. The effectiveness of this new algorithm is tested for three types of molecular photoswitches of significant importance in material and biomedical sciences: photostatin (PST), stilbene, and butadiene. A rudimentary implementation of the algorithm is applied to PST and stilbene, resulting in the discovery of all previously identified MECIs and several new ones. A refined version of the algorithm, combined with a systematic clustering technique, is applied to butadiene, resulting in the identification of an unprecedented number of energetically accessible MECIs. The results demonstrate that the parallel on-the-fly Crystal algorithm is a powerful tool for automated global CI seam exploration.

CREST-A program for the exploration of low-energy molecular chemical space

Conformer-rotamer sampling tool (CREST) is an open-source program for the efficient and automated exploration of molecular chemical space. Originally developed in Pracht et al. [Phys. Chem. Chem. Phys. 22, 7169 (2020)] as an automated driver for calculations at the extended tight-binding level (xTB), it offers a variety of molecular- and metadynamics simulations, geometry optimization, and molecular structure analysis capabilities. Implemented algorithms include automated procedures for conformational sampling, explicit solvation studies, the calculation of absolute molecular entropy, and the identification of molecular protonation and deprotonation sites. Calculations are set up to run concurrently, providing efficient single-node parallelization. CREST is designed to require minimal user input and comes with an implementation of the GFNn-xTB Hamiltonians and the GFN-FF force-field. Furthermore, interfaces to any quantum chemistry and force-field software can easily be created. In this article, we present recent developments in the CREST code and show a selection of applications for the most important features of the program. An important novelty is the refactored calculation backend, which provides significant speed-up for sampling of small or medium-sized drug molecules and allows for more sophisticated setups, for example, quantum mechanics/molecular mechanics and minimum energy crossing point calculations.

Accurate Excitation Energies of Point Defects from Fast Particle-Particle Random Phase Approximation Calculations

We present an efficient particle-particle random phase approximation (ppRPA) approach that predicts accurate excitation energies of point defects, including the nitrogen-vacancy (NV-) and silicon-vacancy (SiV0) centers in diamond and the divacancy center (VV0) in 4H silicon carbide, with errors of ±0.2 eV compared with experimental values. Starting from the (N + 2)-electron ground state calculated with density functional theory (DFT), the ppRPA excitation energies of the N-electron system are calculated as the differences between the two-electron removal energies of the (N + 2)-electron system. We demonstrate that the ppRPA excitation energies converge rapidly with a few hundred canonical active-space orbitals. We also show that active-space ppRPA has weak DFT starting-point dependence and is significantly cheaper than the corresponding ground-state DFT calculation. This work establishes ppRPA as an accurate and low-cost tool for investigating excited-state properties of point defects and opens up new opportunities for applications of ppRPA to periodic bulk materials.

On the description of conical intersections between excited electronic states with LR-TDDFT and ADC(2)

Conical intersections constitute the conceptual bedrock of our working understanding of ultrafast, nonadiabatic processes within photochemistry (and photophysics). Accurate calculation of potential energy surfaces within the vicinity of conical intersections, however, still poses a serious challenge to many popular electronic structure methods. Multiple works have reported on the deficiency of methods like linear-response time-dependent density functional theory within the adiabatic approximation (AA LR-TDDFT) or algebraic diagrammatic construction to second-order [ADC(2)]-approaches often used in excited-state molecular dynamics simulations-to describe conical intersections between the ground and excited electronic states. In the present study, we focus our attention on conical intersections between excited electronic states and probe the ability of AA LR-TDDFT and ADC(2) to describe their topology and topography, using protonated formaldimine and pyrazine as two exemplar molecules. We also take the opportunity to revisit the performance of these methods in describing conical intersections involving the ground electronic state in protonated formaldimine-highlighting in particular how the intersection ring exhibited by AA LR-TDDFT can be perceived either as a (near-to-linear) seam of intersection or two interpenetrating cones, depending on the magnitude of molecular distortions within the branching space.

On the Simulation of Thermal Isomerization of Molecular Photoswitches in Biological Systems

Molecular photoswitches offer precise, reversible photocontrol over biomolecular functions and are promising light-regulated drug candidates with minimal side effects. Quantifying thermal isomerization rates of photoswitches in their target biomolecules is essential for fine-tuning their light-controlled drug activity. However, the effects of protein binding on isomerization kinetics remain poorly understood, and simulations are crucial for filling this gap. Challenges in the simulation include describing multireference electronic structures near transition states, disentangling competing reaction pathways, and sampling protein-ligand interactions. To overcome these challenges, we used multiscale simulations to characterize the thermal isomerization of photostatins (PSTs), which are light-regulated microtubule inhibitors for potential cancer phototherapy. We employed a new ab initio multireference electronic structure method in a quantum mechanics/molecular mechanics setting and combined it with enhanced sampling techniques to characterize the cis to trans free-energy profiles of three PSTs in a vacuum, aqueous solution, and tubulin dimer. The significant advantage of our novel approach is the efficient treatment of the multireference character in PSTs' electronic wavefunction throughout the conformational sampling of protein-ligand interactions along their isomerization pathways. We also benchmarked our calculations using high-level ab initio multireference electronic structure methods and explored the competing isomerization pathways. Notably, calculations in a vacuum and implicit solvent models cannot predict the order of the PSTs' thermal half-lives in the aqueous solution observed in the experiment. Only by explicitly treating the solvent molecules can the correct order of isomerization kinetics be reproduced. Protein binding perturbs free-energy barriers due to hydrogen bonding between PSTs and nearby polar residues. Our work generates comprehensive, high-quality benchmark data and offers guidance for selecting computational methods to study the thermal isomerization of photoswitches. Ab initio multireference free-energy calculations in explicit molecular environments are crucial for predicting the effects of substituents on the thermal half-lives of photoswitches in biological systems.

Linear Scaling Calculations of Excitation Energies with Active-Space Particle-Particle Random-Phase Approximation

We developed an efficient active-space particle-particle random-phase approximation (ppRPA) approach to calculate accurate charge-neutral excitation energies of molecular systems. The active-space ppRPA approach constrains both indexes in particle and hole pairs in the ppRPA matrix, which only selects frontier orbitals with dominant contributions to low-lying excitation energies. It employs the truncation in both orbital indexes in the particle-particle and the hole-hole spaces. The resulting matrix, whose eigenvalues are excitation energies, has a dimension that is independent of the size of the systems. The computational effort for the excitation energy calculation, therefore, scales linearly with system size and is negligible compared with the ground-state calculation of the (N - 2)-electron system, where N is the electron number of the molecule. With the active space consisting of 30 occupied and 30 virtual orbitals, the active-space ppRPA approach predicts the excitation energies of valence, charge-transfer, Rydberg, double, and diradical excitations with the mean absolute errors (MAEs) smaller than 0.03 eV compared with the full-space ppRPA results. As a side product, we also applied the active-space ppRPA approach in the renormalized singles (RS) T-matrix approach. Combining the non-interacting pair approximation that approximates the contribution to the self-energy outside the active space, the active-space GRSTRS@PBE approach predicts accurate absolute and relative core-level binding energies with the MAEs around 1.58 and 0.3 eV, respectively. The developed linear scaling calculation of excitation energies is promising for applications to large and complex systems.

A Dynamically Weighted Constrained Complete Active Space Ansatz for Constructing Multiple Potential Energy Surfaces within the Anderson-Holstein Model

We derive and implement the necessary equations for solving a dynamically weighted, state-averaged constrained CASSCF(2,2) wave function describing a molecule on a metal surface, where we constrain the overlap between two active orbitals and the impurity atomic orbitals to be a finite number. We show that a partial constraint is far more robust than a full constraint. We further calculate the system-bath electronic couplings that arise because, near a metal, there is a continuum (rather than discrete) number of electronic states. This approach should be very useful for simulating heterogeneous electron transfer and electrochemical dynamics going forward.

Deciphering Methylation Effects on S2(ππ*) Internal Conversion in the Simplest Linear α,β-Unsaturated Carbonyl

Chemical substituents can influence photodynamics by altering the location of critical points and the topography of the potential energy surfaces (electronic effect) and by selectively modifying the inertia of specific nuclear modes (inertial effects). Using nonadiabatic dynamics simulations, we investigate the impact of methylation on S₂(ππ*) internal conversion in acrolein, the simplest linear α,β-unsaturated carbonyl. Consistent with time constants reported in a previous time-resolved photoelectron spectroscopy study, S₂ → S₁ deactivation occurs on an ultrafast time scale (∼50 fs). However, our simulations do not corroborate the sequential decay model used to fit the experiment. Instead, upon reaching the S₁ state, the wavepacket bifurcates: a portion undergoes ballistic S₁ → S₀ deactivation (∼90 fs) mediated by fast bond-length alternation motion, while the remaining decays on the picosecond time scale. Our analysis reveals that methyl substitution, generally assumed to mainly exert inertial influence, is also manifested in important electronic effects due to its weak electron-donating ability. While methylation at the β C atom gives rise to effects principally of an inertial nature, such as retarding the twisting motion of the terminal -CHCH₃ group and increasing its coupling with pyramidalization, methylation at the α or carbonyl C atom modifies the potential energy surfaces in a way that also contributes to altering the late S₁-decay behavior. Specifically, our results suggest that the observed slowing of the picosecond component upon α-methylation is a consequence of a tighter surface and reduced amplitude along the central pyramidalization, effectively restricting the access to the S₁/S₀-intersection seam. Our work offers new insight into the S₂(ππ*) internal conversion mechanisms in acrolein and its methylated derivatives and highlights site-selective methylation as a tuning knob to manipulate photochemical reactions.

Finding Excited-State Minimum Energy Crossing Points on a Budget: Non-Self-Consistent Tight-Binding Methods

The automated exploration and identification of minimum energy conical intersections (MECIs) is a valuable computational strategy for the study of photochemical processes. Due to the immense computational effort involved in calculating non-adiabatic derivative coupling vectors, simplifications have been introduced focusing instead on minimum energy crossing points (MECPs), where promising attempts were made with semiempirical quantum mechanical methods. A simplified treatment for describing crossing points between almost arbitrary diabatic states based on a non-self-consistent extended tight-binding method, GFN0-xTB, is presented. Involving only a single diagonalization of the Hamiltonian, the method can provide energies and gradients for multiple electronic states, which can be used in a derivative coupling-vector-free scheme to calculate MECPs. By comparison with high-lying MECIs of benchmark systems, it is demonstrated that the identified geometries are good starting points for further MECI refinement with ab initio methods.

SQMBox: Interfacing a semiempirical integral library to modular ab initio electronic structure enables new semiempirical methods

Ab initio and semiempirical electronic structure methods are usually implemented in separate software packages or use entirely different code paths. As a result, it can be time-consuming to transfer an established ab initio electronic structure scheme to a semiempirical Hamiltonian. We present an approach to unify ab initio and semiempirical electronic structure code paths based on a separation of the wavefunction ansatz and the needed matrix representations of operators. With this separation, the Hamiltonian can refer to either an ab initio or semiempirical treatment of the resulting integrals. We built a semiempirical integral library and interfaced it to the GPU-accelerated electronic structure code TeraChem. Equivalency between ab initio and semiempirical tight-binding Hamiltonian terms is assigned according to their dependence on the one-electron density matrix. The new library provides semiempirical equivalents of the Hamiltonian matrix and gradient intermediates, corresponding to those provided by the ab initio integral library. This enables the straightforward combination of semiempirical Hamiltonians with the full pre-existing ground and excited state functionality of the ab initio electronic structure code. We demonstrate the capability of this approach by combining the extended tight-binding method GFN1-xTB with both spin-restricted ensemble-referenced Kohn-Sham and complete active space methods. We also present a highly efficient GPU implementation of the semiempirical Mulliken-approximated Fock exchange. The additional computational cost for this term becomes negligible even on consumer-grade GPUs, enabling Mulliken-approximated exchange in tight-binding methods for essentially no additional cost.

Multifaceted View on the Mechanism of a Photochemical Deracemization Reaction

Upon irradiation in the presence of a chiral benzophenone catalyst (5 mol %), a racemic mixture of a given chiral imidazolidine-2,4-dione (hydantoin) can be converted almost quantitatively into the same compound with high enantiomeric excess (80-99% ee). The mechanism of this photochemical deracemization reaction was elucidated by a suite of mechanistic experiments. It was corroborated by nuclear magnetic resonance titration that the catalyst binds the two enantiomers by two-point hydrogen bonding. In one of the diastereomeric complexes, the hydrogen atom at the stereogenic carbon atom is ideally positioned for hydrogen atom transfer (HAT) to the photoexcited benzophenone. Detection of the protonated ketyl radical by transient absorption revealed hydrogen abstraction to occur from only one but not from the other hydantoin enantiomer. Quantum chemical calculations allowed us to visualize the HAT within this complex and, more importantly, showed that the back HAT does not occur to the carbon atom of the hydantoin radical but to its oxygen atom. The achiral enol formed in this process could be directly monitored by its characteristic transient absorption signal at λ ≅ 330 nm. Subsequent tautomerization leads to both hydantoin enantiomers, but only one of them returns to the catalytic cycle, thus leading to an enrichment of the other enantiomer. The data are fully consistent with deuterium labeling experiments and deliver a detailed picture of a synthetically useful photochemical deracemization reaction.

Analytical gradients and derivative couplings for the TDDFT-1D method

We derive and implement analytic gradients and derivative couplings for time-dependent density functional theory plus one double (TDDFT-1D) which is a semiempirical configuration interaction method whereby the Hamiltonian is diagonalized in a basis of all singly excited configurations and one doubly excited configuration as constructed from a set of reference Kohn-Sham orbitals. We validate the implementation by comparing against finite difference values. Furthermore, we show that our implementation can locate both optimized geometries and minimum-energy crossing points along conical seams of S₁/S₀ surfaces for a set of test cases.

Multinode Multi-GPU Two-Electron Integrals: Code Generation Using the Regent Language

The computation of two-electron repulsion integrals (ERIs) is often the most expensive step of integral-direct self-consistent field methods. Formally it scales as O(N⁴), where N is the number of Gaussian basis functions used to represent the molecular wave function. In practice, this scaling can be reduced to O(N²) or less by neglecting small integrals with screening methods. The contributions of the ERIs to the Fock matrix are of Coulomb (J) and exchange (K) type and require separate algorithms to compute matrix elements efficiently. We previously implemented highly efficient GPU-accelerated J-matrix and K-matrix algorithms in the electronic structure code TeraChem. Although these implementations supported the use of multiple GPUs on a node, they did not support the use of multiple nodes. This presents a key bottleneck to cutting-edge ab initio simulations of large systems, e.g., excited state dynamics of photoactive proteins. We present our implementation of multinode multi-GPU J- and K-matrix algorithms in TeraChem using the Regent programming language. Regent directly supports distributed computation in a task-based model and can generate code for a variety of architectures, including NVIDIA GPUs. We demonstrate multinode scaling up to 45 GPUs (3 nodes) and benchmark against hand-coded TeraChem integral code. We also outline our metaprogrammed Regent implementation, which enables flexible code generation for integrals of different angular momenta.

Fast Screening of Minimum Energy Crossing Points with Semiempirical Tight-Binding Methods

The investigation of photochemical processes is a highly active field in computational chemistry. One research direction is the automated exploration and identification of minimum energy conical intersection (MECI) geometries. However, due to the immense technical effort required to calculate nonadiabatic potential energy landscapes, the routine application of such computational protocols is severely limited. In this study, we will discuss the prospect of combining adiabatic potential energy surfaces from semiempirical quantum mechanical calculations with specialized confinement potential and metadynamics simulations to identify S₀/T₁ minimum energy crossing point (MECP) geometries. It is shown that MECPs calculated at the GFN2-xTB level can provide suitable approximations to high-level S₀/S₁ab initio conical intersection geometries at a fraction of the computational cost. Reference MECIs of benzene are studied to illustrate the basic concept. An example application of the presented protocol is demonstrated for a set of photoswitch molecules.

Multiscale simulation unravels the light-regulated reversible inhibition of dihydrofolate reductase by phototrexate

Molecular photoswitches are widely used in photopharmacology, where the biomolecular functions are photo-controlled reversibly with high spatiotemporal precision. Despite the success of this field, it remains elusive how the protein environment modulates the photochemical properties of photoswitches. Understanding this fundamental question is critical for designing more effective light-regulated drugs with mitigated side effects. In our recent work, we employed first-principles non-adiabatic dynamics simulations to probe the effects of protein on the trans to cis photoisomerization of phototrexate (PTX), a photochromic analog of the anticancer therapeutic methotrexate that inhibits the target enzyme dihydrofolate reductase (DHFR). Building upon this study, in this work, we employ multiscale simulations to unravel the full photocycle underlying the light-regulated reversible inhibition of DHFR by PTX, which remains elusive until now. First-principles non-adiabatic dynamics simulations reveal that the cis to trans photoisomerization quantum yield is hindered in the protein due to backward isomerization on the ground-state following non-adiabatic transition, which arises from the favorable binding of the cis isomer with the protein. However, free energy simulations indicate that cis to trans photoisomerization significantly decreases the binding affinity of the PTX. Thus, the cis to trans photoisomerization most likely precedes the ligand unbinding from the protein. We propose the most probable photocycle of the PTX-DHFR system. Our comprehensive simulations highlight the trade-offs among the binding affinity, photoisomerization quantum yield, and the thermal stability of the ligand's different isomeric forms. As such, our work reveals new design principles of light-regulated drugs in photopharmacology.

Excited state non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential

Light-induced chemical processes are ubiquitous in nature and have widespread technological applications. For example, photoisomerization can allow a drug with a photo-switchable scaffold such as azobenzene to be activated with light. In principle, photoswitches with desired photophysical properties like high isomerization quantum yields can be identified through virtual screening with reactive simulations. In practice, these simulations are rarely used for screening, since they require hundreds of trajectories and expensive quantum chemical methods to account for non-adiabatic excited state effects. Here we introduce a diabatic artificial neural network (DANN), based on diabatic states, to accelerate such simulations for azobenzene derivatives. The network is six orders of magnitude faster than the quantum chemistry method used for training. DANN is transferable to azobenzene molecules outside the training set, predicting quantum yields for unseen species that are correlated with experiment. We use the model to virtually screen 3100 hypothetical molecules, and identify novel species with high predicted quantum yields. The model predictions are confirmed using high-accuracy non-adiabatic dynamics. Our results pave the way for fast and accurate virtual screening of photoactive compounds.

Variational Density Functional Calculations of Excited States: Conical Intersection and Avoided Crossing in Ethylene Bond Twisting

Theoretical studies of photochemical processes require a description of the energy surfaces of excited electronic states, especially near degeneracies, where transitions between states are most likely. Systems relevant to photochemical applications are typically too large for high-level multireference methods, and while time-dependent density functional theory (TDDFT) is efficient, it can fail to provide the required accuracy. A variational, time-independent density functional approach is applied to the twisting of the double bond and pyramidal distortion in ethylene, the quintessential model for photochemical studies. By allowing for symmetry breaking, the calculated energy surfaces exhibit the correct topology around the twisted-pyramidalized conical intersection even when using a semilocal functional approximation, and by including explicit self-interaction correction, the torsional energy curves are in close agreement with published multireference results. The findings of the present work point to the possibility of using a single determinant time-independent density functional approach to simulate nonadiabatic dynamics, even for large systems where multireference methods are impractical and TDDFT is often not accurate enough.

Static and dynamic Bethe-Salpeter equations in the T-matrix approximation

While the well-established GW approximation corresponds to a resummation of the direct ring diagrams and is particularly well suited for weakly correlated systems, the T-matrix approximation does sum ladder diagrams up to infinity and is supposedly more appropriate in the presence of strong correlation. Here, we derive and implement, for the first time, the static and dynamic Bethe-Salpeter equations when one considers T-matrix quasiparticle energies and a T-matrix-based kernel. The performance of the static scheme and its perturbative dynamical correction are assessed by computing the neutral excited states of molecular systems. A comparison with more conventional schemes as well as other wave function methods is also reported. Our results suggest that the T-matrix-based formalism performs best in few-electron systems where the electron density remains low.

Effects of Enzyme-Ligand Interactions on the Photoisomerization of a Light-Regulated Chemotherapeutic Drug

Molecular photoswitches permit using light to control protein activity with high spatiotemporal resolutions, thereby alleviating the side effects of conventional chemotherapy. However, due to the challenges in probing ultrafast photoisomerization reactions in biological environments, it remains elusive how the protein influences the photochemistry of the photoswitches, which hampers the rational design of light-regulated therapeutics. To overcome this challenge, we employed first-principles nonadiabatic dynamics simulations to characterize the photodynamics of the phototrexate (PTX), a recently developed photoswitchable anticancer chemotherapeutic that reversibly inhibits its target enzyme dihydrofolate reductase (DHFR). Our simulations show that the protein environment impedes the trans to cis photoisomerization of the PTX. The confinement in the ligand-binding cavity slows down the isomerization kinetics and quantum yield of the photoswitch by reshaping its conical intersection, increasing its excited-state free-energy barrier and quenching its local density fluctuations. Also, the protein environment results in a suboptimal binding mode of the photoproduct that needs to undergo large structural rearrangement to effectively inhibit the enzyme. Therefore, we predict that the PTX's trans → cis photoisomerization in solution precedes its binding with the protein, despite the favorable binding energy of the trans isomer. Our findings highlight the importance of the protein environment on the photochemical reactions of the molecular photoswitches. As such, our work represents an important step toward the rational design of light-regulated drugs in photopharmacology.

Multireference Density Functional Theory for Describing Ground and Excited States with Renormalized Singles

We applied renormalized singles (RS) in the multireference density functional theory (DFT) to calculate accurate energies of ground and excited states. The multireference DFT approach determines the total energy of the N-electron system as the sum of the (N - 2)-electron energy from a density functional approximation (DFA) and the two-electron addition energies from the particle-particle Tamm-Dancoff approximation (ppTDA), naturally including multireference description. The ppTDA@RS-DFA approach uses the RS Hamiltonian capturing all singles contributions in calculating two-electron addition energies, and its total energy is optimized with the optimized effective potential method. It significantly improves the original ppTDA@DFA. For ground states, ppTDA@RS-DFA properly describes dissociation curves tested and the double bond rotation of ethylene. For excited states, ppTDA@RS-DFA provides accurate excitation energies and largely eliminates the DFA dependence. ppTDA@RS-DFA thus provides an efficient multireference approach to systems with static correlation.

Protein confinement fine-tunes aggregation-induced emission in human serum albumin

Luminogens exhibiting aggregation-induced-emission characteristics (AIEgens) have been designed as sensitive biosensors thanks to their "turn-on" fluorescence upon target binding. However, their AIE mechanism in biomolecules remains elusive except for the qualitative picture of restricted intramolecular motions. In this work, we employed ab initio simulations to investigate the AIE mechanism of two tetraphenylethylene derivatives recently developed for sensitive detection of human serum albumin (HSA) in biological fluids. For the first time, we quantified the ab initio free energy surfaces and kinetics of AIEgens to access the conical intersections on the excited state in the protein and aqueous solution, using a novel first-principles electronic structure method that incorporates both static and dynamic electron correlations. Our simulations accurately reproduce the experimental spectra and high-level correlated electronic structure calculations. We found that in HSA the internal conversion through the cyclization reaction is preferred over the isomerization around the central ethylenic double bond, whereas in the aqueous solution the reverse is true. Accordingly, the protein environment is able to moderately speed up certain non-radiative decay pathways, a new finding that is beyond the prediction of the existing model of restricted access to a conical intersection (RACI). As such, our findings highlight the complicated effects of the protein confinement on the competing non-radiative decay channels, which has been largely ignored so far, and extend the existing theories of AIE to biological systems. The new insights and the multiscale computational methods used in this work will aid the design of sensitive AIEgens for bioimaging and disease diagnosis.

Predictions of Pre-edge Features in Time-Resolved Near-Edge X-ray Absorption Fine Structure Spectroscopy from Hole-Hole Tamm-Dancoff-Approximated Density Functional Theory

Time-resolved near-edge X-ray absorption fine structure (TR-NEXAFS) spectroscopy is a powerful technique for studying photochemical reaction dynamics with femtosecond time resolution. In order to avoid ambiguity in TR-NEXAFS spectra from nonadiabatic dynamics simulations, core- and valence-excited states must be evaluated on equal footing and those valence states must also define the potential energy surfaces used in the nonadiabatic dynamics simulation. In this work, we demonstrate that hole-hole Tamm-Dancoff-approximated density functional theory (hh-TDA) is capable of directly simulating TR-NEXAFS spectroscopies. We apply hh-TDA to the excited-state dynamics of acrolein. We identify two pre-edge features in the oxygen K-edge TR-NEXAFS spectrum associated with the S₂ (ππ*) and S₁ (nπ*) excited states. We show that these features can be used to follow the internal conversion dynamics between the lowest three electronic states of acrolein. Due to the low, O(N²) apparent computational complexity of hh-TDA and our GPU-accelerated implementation, this method is promising for the simulation of pre-edge features in TR-NEXAFS spectra of large molecules and molecules in the condensed phase.

On the inclusion of one double within CIS and TDDFT

We present an improved approach for generating a set of optimized frontier orbitals (HOMO and LUMO) that minimizes the energy of one double configuration. We further benchmark the effect of including such a double within a rigorous configuration interaction singles or a parameterized semi-empirical time-dependent density functional theory Hamiltonian for a set of test cases. Although we cannot quite achieve quantitative accuracy, the algorithm is quite robust and routinely delivers an enormous qualitative improvement to standard single-reference electronic structure calculations.

Machine Learning for Electronically Excited States of Molecules

Electronically excited states of molecules are at the heart of photochemistry, photophysics, as well as photobiology and also play a role in material science. Their theoretical description requires highly accurate quantum chemical calculations, which are computationally expensive. In this review, we focus on not only how machine learning is employed to speed up such excited-state simulations but also how this branch of artificial intelligence can be used to advance this exciting research field in all its aspects. Discussed applications of machine learning for excited states include excited-state dynamics simulations, static calculations of absorption spectra, as well as many others. In order to put these studies into context, we discuss the promises and pitfalls of the involved machine learning techniques. Since the latter are mostly based on quantum chemistry calculations, we also provide a short introduction into excited-state electronic structure methods and approaches for nonadiabatic dynamics simulations and describe tricks and problems when using them in machine learning for excited states of molecules.

Machine Learning for Electronically Excited States of Molecules

Electronically excited states of molecules are at the heart of photochemistry, photophysics, as well as photobiology and also play a role in material science. Their theoretical description requires highly accurate quantum chemical calculations, which are computationally expensive. In this review, we focus on not only how machine learning is employed to speed up such excited-state simulations but also how this branch of artificial intelligence can be used to advance this exciting research field in all its aspects. Discussed applications of machine learning for excited states include excited-state dynamics simulations, static calculations of absorption spectra, as well as many others. In order to put these studies into context, we discuss the promises and pitfalls of the involved machine learning techniques. Since the latter are mostly based on quantum chemistry calculations, we also provide a short introduction into excited-state electronic structure methods and approaches for nonadiabatic dynamics simulations and describe tricks and problems when using them in machine learning for excited states of molecules.

Electronic Structure Methods for the Description of Nonadiabatic Effects and Conical Intersections

Nonadiabatic effects are ubiquitous in photophysics and photochemistry, and therefore, many theoretical developments have been made to properly describe them. Conical intersections are central in nonadiabatic processes, as they promote efficient and ultrafast nonadiabatic transitions between electronic states. A proper theoretical description requires developments in electronic structure and specifically in methods that describe conical intersections between states and nonadiabatic coupling terms. This review focuses on the electronic structure aspects of nonadiabatic processes. We discuss the requirements of electronic structure methods to describe conical intersections and nonadiabatic couplings, how the most common excited state methods perform in describing these effects, and what the recent developments are in expanding the methodology and implementing nonadiabatic couplings.

First-Principles Nonadiabatic Dynamics Simulation of Azobenzene Photodynamics in Solutions

The photoisomerization of azobenzene is a prototypical reaction of various light-activated processes in material and biomedical sciences. However, its reaction mechanism has been under debate for decades, partly due to the challenges in computational simulations to accurately describe the molecule's photodynamics. A recent study (J. Am. Chem. Soc. 2020, 142 (49), 20,680-20,690) addressed the challenges by combining the hole-hole Tamm-Dancoff Approximated (hh-TDA) density functional theory (DFT) method with the ab initio multiple spawning (AIMS) algorithm. The hh-TDA-DFT/AIMS method was applied to first-principles nonadiabatic dynamics simulation of azobenzene's photodynamics in the vacuum. However, it remains necessary to benchmark this new method in realistic molecular environments against experimental data. In the current work, the hh-TDA-DFT/AIMS method was employed in a quantum mechanics/molecular mechanics setting to characterize the trans azobenzene's photodynamics in explicit methanol and n-hexane solvents, following both the S₁ (nπ*) and S₂ (ππ*) excitations. The simulated absorption and fluorescence spectra following the S₂ excitation quantitatively agree with the experiments. However, the hh-TDA-DFT method overestimates the torsional barrier on the S₁ state, leading to an overestimation of the S₁ state lifetime. The excited-state population decays to the ground state through two competing channels. The reactive channel partially yields the cis azobenzene photoproduct, and the unreactive channel exclusively leads to the reactant. The S₂ excitation increases the decay through the unreactive channel and thus decreases the isomerization quantum yield compared to the S₁ excitation. The solvent slows down the azobenzene's torsional dynamics on the S₁ state, but its polarity minimally affects the reaction kinetics and quantum yields. Interestingly, the dynamics of the central torsion and angles of azobenzene play a critical role in determining the final isomer of the azobenzene. This benchmark study validates the hh-TDA-DFT/AIMS method's accuracy for simulating the azobenzene's photodynamics in realistic molecular environments.