Calculation Of Molecular Properties Research Articles

Diagrams in Polaritonic Coupled Cluster Theory.

We present a diagrammatic notation to derive the quantum-electrodynamic coupled cluster (QED-CC) equations needed for the description for polaritonic ground and excited states. Our presented notation is a generalization of the existing diagrammatic notation of standard electronic coupled-cluster theory. It is used to derive the QED-CC and QED-EOM-CC equations for the QED-CCSD-1-SD and QED-CCSD-12-SD truncation schemes. Furthermore, we present the diagrams for the CC Λ-equations and reduced density matrices which are needed for the calculation of molecular properties.

Computational study of substituent effects on molecular structure, vibrational and electronic properties of fluorene molecule using density functional theory

Density functional theory (DFT) provides a powerful tool for investigating the effects of halogen (F, Cl and Br) substitution on the electronic and structural properties of fluorene. The B3LYP/6-31G (d,p) protocol is a commonly used method in DFT calculations for the optimisation of molecular structures and the calculation of various molecular properties by Gaussian 09 W program. In the case of the fluorene molecule with halogen substitutions, (TD–DFT) calculations can be used to predict its UV–Vis spectrum. The B3LYP density functional model with a 6-31G(d,p) basis set is a common choice for performing (TD–DFT) calculations on molecules. The results showed a decrease in gap energies when electron-withdrawing groups were present in the molecule. A decrease in the gap energy indicates that the molecule is less stable and more reactive.

Getaway from the Geometry Factor Error in the Molecular Property Calculations: Efficient pecG-n (n = 1, 2) Basis Sets for the Geometry Optimization of Molecules Containing Light p Elements.

The basis of all molecular property quantum chemical calculations is the correct equilibrium geometry. In this paper, new efficient pecG-n (n = 1, 2) basis sets for the geometry optimization of molecules containing hydrogen and p elements of 2-3 periods are proposed. These basis sets were optimized via the property-energy consistent (PEC) algorithm directed to the minimization of the molecular energy gradient relative to the bond lengths. New basis sets are compact and give equilibrium geometries of very high quality, which is comparable to that provided by considerably larger energy-optimized basis sets. The equilibrium geometries obtained with the pecG-n (n = 1, 2) basis sets and the other basis sets of diverse quality were tested in the CCSD calculations of different second-order molecular properties, including NMR shielding constants, static polarizabilities, and static magnetizabilities. As a result, new basis sets have demonstrated far superior performance as compared to the other energy-optimized basis sets of the same or close sizes commonly used at the geometry optimization stage.

STUDYING THE HYPOLYPIDEMIC ACTIVITY OF FLAVONOIDS AND ISOFLAVONOIDS OF THE ONONIS ARVENSIS L. METHODS BY IN SILICO

Introduction. Today, one of the reliably known causes of mortality in the Russian Federation is diseases of the cardiovascular system, a significant part of which is associated with atherosclerotic disease. Combination therapy for diseases of the cardiovascular system includes, among other things, the use of modern lipid-lowering drugs, the use of which is often limited due to their pronounced side effects. In this regard, it seemed appropriate to search for new compounds of natural origin that potentially have lipid-lowering activity with minimal side effects. According to the scientific literature, natural phenolic compounds, namely substances from the group of flavonoids and isoflavonoids, have a set of such characteristics. In this regard, steelgrass (Ononis arvensis L.), the chemical composition of which is extremely rich and diverse in terms of flavonoids and isoflavonoids, can be a ra-ther promising source for searching and screening compounds with a given activity. The aim of the study. The purpose of the work was to study and predict the hypolipidemic activity of flavonoids and isoflavonoids of Ononis arvensis L. using in silico methods. Material and methods. The objects of the study were the structural formulas of flavonoids and isoflavonoids of field steelhead. Calculation of mo-lecular properties was carried out using the Molinspiration chemoinformatic software. Computer prediction of lipid-lowering activity was carried out us-ing the PASS-online service. Molecular docking was performed using the CB-Dock2 services for blind docking and Webina 1.0.5 for active site docking. Hepatotoxicity, mutagenicity and cytotoxicity of the analyzed biologically active substances were studied using the ProTox-II resource. Results. As a result of in silico studies, it was found that most of the studied flavonoids and isoflavonoids correspond to the Lipinski rule and the drug-likeness concept. In addition, for all studied biologically active substances, activities associated with a decrease in lipid fractions in the body were predicted. The results of molecular docking indicate that all analyzed compounds are capable of potentially inhibiting the enzyme HMG-CoA reductase, which makes it possible to predict the required lipid-lowering effect. Studying the toxicity of the research objects, most of them in silico demonstrated a high level of safety. Conclusions. The prospects for further research on the development of targeted technology for obtaining herbal preparations from steelhead, enriched with flavonoids and isoflavonoids, as well as subsequent tests to confirm hypolipidemic activity in in vitro and in vivo experiments are shown.

FROG: Exploiting all-atom molecular dynamics trajectories to calculate linear and non-linear optical responses of molecular liquids within Dalton's QM/MM polarizable embedding scheme.

Quantum mechanical/molecular mechanics (QM/MM) methods are interesting to model the impact of a complex environment on the spectroscopic properties of a molecule. In this context, a FROm molecular dynamics to second harmonic Generation (FROG) code is a tool to exploit molecular dynamics trajectories to perform QM/MM calculations of molecular optical properties. FROG stands for "FROm molecular dynamics to second harmonic Generation" since it was developed for the calculations of hyperpolarizabilities. These are relevant to model non-linear optical intensities and compare them with those obtained from second harmonic scattering or second harmonic generation experiments. FROG's specificity is that it is designed to study simple molecular liquids, including solvents or mixtures, from the bulk to the surface. For the QM/MM calculations, FROG relies on the Dalton package: its electronic-structure models, response theory, and polarizable embedding schemes. FROG helps with the global workflow needed to deal with numerous QM/MM calculations: it permits the user to separate the system into QM and MM fragments, to write Dalton's inputs, to manage the submission of QM/MM calculations, to check whether Dalton's calculation finished successfully, and finally to perform averages on relevant QM observables. All molecules within the simulation box and several time steps are tackled within the same workflow. The platform is written in Python and installed as a package. Intermediate data such as local electric fields or individual molecular properties are accessible to the users in the form of Python object arrays. The resulting data are easily extracted, analyzed, and visualized using Python scripts that are provided in tutorials.

Quantum Equation of Motion with Orbital Optimization for Computing Molecular Properties in Near-Term Quantum Computing.

Determining the properties of molecules and materials is one of the premier applications of quantum computing. A major question in the field is how to use imperfect near-term quantum computers to solve problems of practical value. Inspired by the recently developed variants of the quantum counterpart of the equation-of-motion (qEOM) approach and the orbital-optimized variational quantum eigensolver (oo-VQE), we present a quantum algorithm (oo-VQE-qEOM) for the calculation of molecular properties by computing expectation values on a quantum computer. We perform noise-free quantum simulations of BeH2 in the series of STO-3G/6-31G/6-31G* basis sets and of H4 and H2O in 6-31G using an active space of four electrons and four spatial orbitals (8 qubits) to evaluate excitation energies, electronic absorption, and, for twisted H4, circular dichroism spectra. We demonstrate that the proposed algorithm can reproduce the results of conventional classical CASSCF calculations for these molecular systems.

A variational reformulation of molecular properties in electronic-structure theory.

Conventional quantum-mechanical calculations of molecular properties, such as dipole moments and electronic excitation energies, give errors that depend linearly on the error in the wave function. An exception is the electronic energy, whose error depends quadratically on the error in wave function. We here describe how all properties may be calculated with a quadratic error, by setting up a variational Lagrangian for the property of interest. Because the construction of the Lagrangian is less expensive than the calculation of the wave function, this approach substantially improves the accuracy of quantum-chemical calculations without increasing cost. As illustrated for excitation energies, this approach enables the accurate calculation of molecular properties for larger systems, with a short time-to-solution and in a manner well suited for modern computer architectures.

ZORA Basis Sets of 5 and 6 Zeta Valence Qualities for H-Ar: Application in Calculations of Atomic and Molecular Properties

ZORA Basis Sets of 5 and 6 Zeta Valence Qualities for H-Ar: Application in Calculations of Atomic and Molecular Properties

Design, synthesis, and bioevaluation of novel unsaturated cyanoacetamide derivatives: In vitro and in silico exploration

In this study, we synthesized novel α,β-unsaturated 2-cyanoacetamide derivatives (1–5) using microwave-assisted Knoevenagel condensation. Characterization of these compounds was carried out using FTIR and 1H NMR spectroscopy. We then evaluated their in vitro antibacterial activity against both gram-positive and gram-negative pathogenic bacteria. Additionally, we employed in silico methods, including ADMET prediction and density functional theory (DFT) calculations of molecular orbital properties, to investigate these cyanoacetamide derivatives (1–5). Molecular docking was used to assess the binding interactions of these derivatives (1–5) with seven target proteins (5MM8, 4NZZ, 7FEQ, 5NIJ, ITM2, 6SE1, and 5GVZ) and compared them to the reference standard tyrphostin AG99. Notably, derivative 5 exhibited the most favorable binding affinity, with a binding energy of -7.7 kcal mol−1 when interacting with the staphylococcus aureus (PDB:5MM8), while also meeting all drug-likeness criteria. Additionally, molecular dynamics simulations were carried out to evaluate the stability of the interaction between the protein and ligand, utilizing parameters such as Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), Radius of Gyration (Rg), and Principal Component Analysis (PCA). A 50 nanosecond molecular dynamics (MD) simulation was performed to investigate stability further, incorporating RMSD and RMSF analyses on compound 5 within the active binding site of the modeled protein across different temperatures (300, 305, 310, and 320 K). Among these temperatures, compound 5 exhibited an RMSD value ranging from approximately 0.2 to 0.3 nm at 310 K (body temperature) with the 5MM8 target, which differed from the other temperature conditions. The in silico results suggest that compound 5 maintained significant conformational stability throughout the 50 ns simulation period. It is consistent with its low docking energy and in vitro findings concerning α,β-unsaturated cyanoacetamides.Key insights from this study include:•The creation of innovative α,β-unsaturated 2-cyanoacetamide derivatives (1–5) employing cost-effective, licensed, versatile, and efficient software for both in silico and in vitro assessment of antibacterial activity.•Utilization of FTIR and NMR techniques for characterizing compounds 1–5.

Quantum computing for electronic structure analysis: Ground state energy and molecular properties calculations

The computation of electronic structure properties at the quantum level is a crucial aspect of modern physics research. However, conventional methods can be computationally demanding for larger, more complex systems. To address this issue, we present a hybrid Classical-Quantum computational procedure that uses the Variational Quantum Eigensolver (VQE) algorithm. By mapping the quantum system to a set of qubits and utilising a quantum circuit to prepare the ground state wavefunction, our algorithm offers a streamlined process requiring fewer computational resources than classical methods. Our algorithm demonstrated similar accuracy in rigorous comparisons with conventional electronic structure methods, such as Density Functional Theory and Hartree–Fock Theory, on a range of molecules while utilising significantly fewer resources. These results indicate the potential of the algorithm to expedite the development of new materials and technologies. This work paves the way for overcoming the computational challenges of electronic structure calculations. It demonstrates the transformative impact of quantum computing on advancing our understanding of complex quantum systems.

RotGT-2023: A benchmark data set of rotational g tensors.

The largest ever set, RotGT-2023, of statistically validated experimental components of rotational g tensors and respective vibrational corrections, has been created. The experimental values were collected from literature data. The vibrational corrections for obtaining equilibrium molecular g values have been calculated at the highest affordable coupled cluster level of theory. The set comprises 278 parameters from 129 molecules, including their isotopologues. Statistical assessment of the data has been performed to exclude unreliable parameters. A benchmarking of two theoretical approximations, based on coupled cluster and density functional theories, has been performed. The determined weighted mean and weighted standard deviations of the relative errors in calculated equilibrium g values are 1.09% and 2.07% for the ae-CCSD(T)/x2c-TZVPPall-s//ae-CCSD(T)/cc-pwCVTZ level. The obtained results can be used for predicting the rotational Zeeman effect, correcting rotational constants in spectroscopic studies and in molecular structure refinements. The latter has been demonstrated on the refinement of the molecular structure of silane SiH4, which resulted in rese(Si-H) = 1.473 323 1(27) Å. The other tested theoretical protocol, PBE0/x2c-TZVPPall-s//PBE0-D3BJ/def2-QZVPP, showed considerably worse statistical properties. The RotGT-2023 data set and the developed in this work statistical model are recommended for benchmarking of theoretical approximations for calculations of molecular magnetic properties.

Accurate Potential Energy Surfaces Using Atom-Centered Potentials and Minimal High-Level Data.

We demonstrate that a Δ-density functional theory (Δ-DFT) approach based on atom-centered potentials (ACPs) represents a computationally inexpensive and accurate method for representing potential energy surfaces (PESs) for the HONO and HFCO molecules and vibrational frequencies derived therefrom. Using as few as 100 CCSD(T)-F12a reference energies, ACPs developed for use with B3LYP/def2-TZVPP are shown to produce PESs for HONO and HFCO with mean absolute errors of 27.7 and 5.8 cm-1, respectively. Application of the multiconfigurational time-dependent Hartree (MCTDH) method with ACP-corrected B3LYP/def2-TZVPP PESs produces vibrational frequencies for cis- and trans-HONO with mean absolute percent errors (MAPEs) of 0.8 and 1.1, compared to 0.8 obtained for the two isomers with CCSD(T)-F12a/cc-pVTZ-F12/MCTDH. For HFCO, the vibrational frequencies obtained using the present (Δ-DFT)/MCTDH approach give a MAPE of 0.1, which is the error obtained with CCSD(T)-F12a/cc-pVTZ-F12/MCTDH. The ACP approach is therefore successful in representing a PES calculated at a high level of theory (CCSD(T)-F12a) and a promising method for the development of a general protocol for the representation of accurate molecular PESs and the calculation of molecular properties from them.

Solving response expressions in the ADC/ISR framework.

We present an implementation for the calculation of molecular response properties using the algebraic-diagrammatic construction (ADC)/intermediate state representation approach. For the second-order ADC model [ADC(2)], a memory-efficient ansatz avoiding the storage of double excitation amplitudes is investigated. We compare the performance of different numerical algorithms for the solution of the underlying response equations for ADC(2) and show that our approach also strongly improves the convergence behavior for the investigated algorithms compared with the standard implementation. All routines are implemented in an open-source Python library.

Application of Machine Learning to the Design of Energetic Materials: Preliminary Experience and Comparison with Alternative Techniques

AbstractThe last few years have seen a steep rise in the use of data‐driven methods in different scientific fields historically relying on theoretical or empirical approaches. Chemistry is at the forefront of this paradigm shift due to the longstanding use of computational tools involved in the calculation of molecular structures and properties. In this paper, we showcase examples from the literature as well as work in progress in our lab in order to give a brief overview on how these methods can benefit the energetic materials community. A deep learning approach is compared to “traditional” QSPR and semi‐empirical approaches for molecular property prediction, and specificities inherent to energetic materials are discussed. Deep generative models for the design of new energetic materials are also presented. We conclude by giving our view on the most promising strategies for future in silico generation of new energetic materials satisfying the performance/sensitivity trade‐off.

Calculations of molecular properties of 2-(2'-hydroxyphenyl)benzoxazole by semi-empirical tight-binding methods

The semi-empirical tight-binding methods GFN1-xTB and GFN2-xTB are applied to calculations of structure, energy and normal vibrations of the molecule of 2-(2'-hydroxyphenyl)benzoxazole undergoing excited state intramolecular proton transfer. The results are compared with ones obtained by the density-functional tight-binding methods with hydrogen interaction corrections and density functional theory. The GFN2-xTB method is found to provide good correspondence to the results obtained by more accurate but much slower density functional theory method for geometrical parameters of hydrogen bond, relative energy of molecular conformations and potential energy surface.

Molecular-excited-state calculations with the qubit-excitation-based adaptive variational quantum eigensolver protocol

Calculations of molecular spectral properties, like photodissociation rates and absorption bands, rely on knowledge of the excited state energies of the molecule of interest. Protocols based on the variational quantum eigensolver (VQE) are promising candidates to calculate such energies on emerging noisy intermediate-scale quantum (NISQ) computers. The successful implementation of these protocols on NISQ computers, relies on ans\"atze that can accurately approximate the molecular states and that can be implemented by shallow quantum circuits. We introduce the excited qubit-excitation-based adaptive (e-QEB-ADAPT)-VQE protocol to calculate molecular-excited-state energies. The e-QEB-ADAPT-VQE constructs efficient problem-tailored ans\"atze by iteratively appending evolutions of qubit excitation operators. The e-QEB-ADAPT-VQE also improves on previous ADAPT-VQE protocol in that it is designed to be independent on the choice of initial reference state. We perform classical numerical simulations for LiH and ${\mathrm{BeH}}_{2}$ to benchmark the performance of the e-QEB-ADAPT-VQE. We demonstrate that the e-QEB-ADAPT-VQE can construct highly accurate ans\"atze that require at least an order of magnitude fewer cnot gates than standard fixed unitary coupled-cluster ans\"atze, such as the UCCSD and the GUCCSD. We also show that the e-QEB-ADAPT-VQE is more successful in constructing ans\"atze for excited molecular states than other ADAPT-VQE protocols.

Best-Practice DFT Protocols for Basic Molecular Computational Chemistry.

Nowadays, many chemical investigations are supported by routine calculations of molecular structures, reaction energies, barrier heights, and spectroscopic properties. The lion's share of these quantum-chemical calculations applies density functional theory (DFT) evaluated in atomic-orbital basis sets. This work provides best-practice guidance on the numerous methodological and technical aspects of DFT calculations in three parts: Firstly, we set the stage and introduce a step-by-step decision tree to choose a computational protocol that models the experiment as closely as possible. Secondly, we present a recommendation matrix to guide the choice of functional and basis set depending on the task at hand. A particular focus is on achieving an optimal balance between accuracy, robustness, and efficiency through multi-level approaches. Finally, we discuss selected representative examples to illustrate the recommended protocols and the effect of methodological choices.

Best‐Practice DFT Protocols for Basic Molecular Computational Chemistry**

AbstractNowadays, many chemical investigations are supported by routine calculations of molecular structures, reaction energies, barrier heights, and spectroscopic properties. The lion's share of these quantum‐chemical calculations applies density functional theory (DFT) evaluated in atomic‐orbital basis sets. This work provides best‐practice guidance on the numerous methodological and technical aspects of DFT calculations in three parts: Firstly, we set the stage and introduce a step‐by‐step decision tree to choose a computational protocol that models the experiment as closely as possible. Secondly, we present a recommendation matrix to guide the choice of functional and basis set depending on the task at hand. A particular focus is on achieving an optimal balance between accuracy, robustness, and efficiency through multi‐level approaches. Finally, we discuss selected representative examples to illustrate the recommended protocols and the effect of methodological choices.

Heterogeneous relational message passing networks for molecular dynamics simulations

With many frameworks based on message passing neural networks proposed to predict molecular and bulk properties, machine learning methods have tremendously shifted the paradigms of computational sciences underpinning physics, material science, chemistry, and biology. While existing machine learning models have yielded superior performances in many occasions, most of them model and process molecular systems in terms of homogeneous graph, which severely limits the expressive power for representing diverse interactions. In practice, graph data with multiple node and edge types is ubiquitous and more appropriate for molecular systems. Thus, we propose the heterogeneous relational message passing network (HermNet), an end-to-end heterogeneous graph neural networks, to efficiently express multiple interactions in a single model with ab initio accuracy. HermNet performs impressively against many top-performing models on both molecular and extended systems. Specifically, HermNet outperforms other tested models in nearly 75%, 83% and 69% of tasks on revised Molecular Dynamics 17 (rMD17), Quantum Machines 9 (QM9) and extended systems datasets, respectively. In addition, molecular dynamics simulations and material property calculations are performed with HermNet to demonstrate its performance. Finally, we elucidate how the design of HermNet is compatible with quantum mechanics from the perspective of the density functional theory. Besides, HermNet is a universal framework, whose sub-networks could be replaced by other advanced models.

Coupling density functional based tight binding with class 1 force fields in a hybrid QM/MM scheme

Quantum Mechanics/Molecular Mechanics (QM/MM) hybrid methods have become very popular schemes to incorporate environmental effects in the calculation of molecular properties, when it is mandatory to have both a quantum description of electrons to compute these properties and an atomistic description of the environment. However, even Density Functional Theory/MM schemes may become timecosting when a large part of the system should be treated at the QM level or when plenty of single point energy calculations are intended to be done. We report a new implementation, within the deMonNano code, of a hybrid QM/MM scheme combining the density functional based tight binding with class 1 force fields. Two types of additive couplings can be chosen, namely the mechanical coupling, consisting of a Lennard-Jones potential and the electrostatic coupling, in which the MM part of the system is also polarizing the region described at the QM level. As first test-case application, the harmonic infrared spectra of simple molecules in the gas phase and in water clusters are computed and compared to those obtained at the DFT/MM level. Binding energies are also compared. Similar trends are obtained with the two levels of calculations and the main differences are discussed.