Fitting Molecular Electrostatic Potentials from Quantum Mechanical Calculations

Quantum Chemical and Biological Insights into Redox Activity of Metallacarborane Complexes in Cancer Cells

A relationship between the electronic properties of metal ions in metallacarboranes and their ability to modulate mitochondrial oxidase activity and membrane hyperpolarization in cancer cells was demonstrated. Quantum chemistry methods, including DFT and molecular dynamics simulations, were used to understand the oxidized and reduced forms of metallacarboranes and their intramolecular rotatory behavior. According to the low-spin assumption for metal ions, the intramolecular oscillations of cluster ligands in metallacarboranes are significantly influenced by the type of metal and correspond to the cellular uptake of these complexes in vitro. In particular, the low-spin iron compound may be a new xenogeneic booster of redox homeostasis in cancer cells resistant to cisplatin, which induces metabolic 'exhaustion' of cancer cells and their death.

Stabilization of the Protein Structure by the Many-Body Cooperative Effect in the NH/π Hydrogen-bonding Tryptophan Triad

The indole ring of tryptophan can form NH/π hydrogen bonds, acting both as a hydrogen donor at the NH group in the pyrrole subring and as a hydrogen acceptor at the benzene subring. In the structural core of the trimeric stable protein Pholiota squarrosa lectin (PhoSL), three indoles are symmetrically arranged and form NH/π hydrogen bonds among each other. Here, we conducted quantum chemical calculations on this indole triad by using various methods and basis sets. The analyses revealed cooperativity in triad formation, with the many-body effect contributing approximately -2 kcal mol-1, which significantly stabilizes this protein. Symmetry-adapted perturbation theory ascribed this effect to the induced polarization. The electrostatic potential and atomic charges indeed revealed a charge redistribution through the NH/π hydrogen bond, which was favorable for triad formation.

The Separability Problem in Molecular Quantum Systems: Information-Theoretic Framework for Atoms in Molecules

Even though molecules are fundamentally quantum entities, the concept of a molecule retains certain classical attributes concerning its constituents. This includes the empirical separability of a molecule into its three-dimensional, rigid structure in Euclidean space, a framework often obtained through experimental methods like X-Ray crystallography. In this work, we delve into the mathematical implications of partitioning a molecule into its constituent parts using the widely recognized Atoms-In-Molecules (AIM) schemes, aiming to establish their validity within the framework of Information Theory concepts. We have uncovered information-theoretical justifications for employing some of the most prevalent AIM schemes in the field of Chemistry, including Hirshfeld (stockholder partitioning), Bader's (topological dissection), and the quantum approach (Hilbert's space definition). In the first approach we have applied the generalized principle of minimum relative entropy derived from the Sharma-Mittal two-parameter functional, avoiding the need for an arbitrary selection of reference promolecular atoms. Within the ambit of topological-information partitioning, we have demonstrated that the Fisher information of Bader's atoms conform to a comprehensive theory based on the Principle of Extreme Physical Information avoiding the need of employing the Schwinger's principle, which has been proven to be problematic. For the quantum approach we have presented information-theoretic justifications for conducting Löwdin symmetric transformations on the density matrix to form atomic Hilbert spaces generating orthonormal atomic orbitals with maximum occupancy for a given wavefunction.

Excitonic Configuration Interaction: Going Beyond the Frenkel Exciton Model

We present the excitonic configuration interaction (ECI) method─a fragment-based analogue of the CI method for electronic structure calculations of multichromophoric systems. It can also be viewed as a generalization of the exciton approach, with the following properties: (i) It constructs the effective Hamiltonian exclusively from monomer calculations. (ii) It employs the strong orthogonality assumption and is exact within McWeeny's group function theory, thus requiring only one-electron density matrices of the monomer states. (iii) It is agnostic of the monomer electronic structure method, allowing us to use/combine different methods. (iv) It includes an embedding point charge scheme (called excitonic Hartree-Fock, EHF) to improve the accuracy of the monomer states, but such that the effective full-system Hamiltonian is not explicitly dependent on the embedding. (v) It is systematically improvable, by expanding the set of monomer states and by including configurations where two or more monomers are excited (defining the ECIS, ECISD, etc., methods). The performance of ECI is assessed by computing the absorption spectrum of two exemplary multichromophoric systems, using CIS as the monomer electronic structure method. The accuracy of ECI significantly depends on the chosen embedding charges and the ECI expansion. The most accurate assessed combinations─ECIS or ECISD with EHF embedding─yield spectra that agree qualitatively and quantitatively with full-system direct calculations, with deviations of the excitation energies below 0.1 eV. We also show that ECISD based on CIS monomer calculations can predict states where two monomers are excited simultaneously (e.g., triplet-triplet double-local excitations) that are inaccessible in a full-system CIS calculation.

Bottom-Up Atomistic Descriptions of Top-Down Macroscopic Measurements: Computational Benchmarks for Hammett Electronic Parameters

The ability to relate substituent electronic effects to chemical reactivity is a cornerstone of physical organic chemistry and Linear Free Energy Relationships. The computation of electronic parameters is increasingly attractive since they can be obtained rapidly for structures and substituents without available experimental data and can be applied beyond aromatic substituents, for example, in studies of transition metal complexes and aliphatic and radical systems. Nevertheless, the description of "top-down" macroscopic observables, such as Hammett parameters using a "bottom-up" computational approach, poses several challenges for the practitioner. We have examined and benchmarked the performance of various computational charge schemes encompassing quantum mechanical methods that partition charge density, methods that fit charge to physical observables, and methods enhanced by semiempirical adjustments alongside NMR values. We study the locations of the atoms used to obtain these descriptors and their correlation with empirical Hammett parameters and rate differences resulting from electronic effects. These seemingly small choices have a much more significant impact than previously imagined, which outweighs the level of theory or basis set used. We observe a wide range of performance across the different computational protocols and observe stark and surprising differences in the ability of computational parameters to capture para- vs meta-electronic effects. In general, σm predictions fare much worse than σp. As a result, the choice of where to compute these descriptors-for the ring carbons or the attached H or other substituent atoms-affects their ability to capture experimental electronic differences. Density-based schemes, such as Hirshfeld charges, are more stable toward unphysical charge perturbations that result from nearby functional groups and outperform all other computational descriptors, including several commonly used basis set based schemes such as Natural Population Analysis. Using attached atoms also improves the statistical correlations. We obtained general linear relationships for the global prediction of experimental Hammett parameters from computed descriptors for use in statistical modeling studies.

On the sensitivity of computed partial charges toward basis set and (exchange-)correlation treatment

Partial charges are a central concept in general chemistry and chemical biology, yet dozens of different computational definitions exist. In prior work [Cho et al., ChemPhysChem 21, 688-696 (2020)], we showed that these can be reduced to at most three 'principal components of ionicity'. The present study addressed the dependence of computed partial charges q on 1-particle basis set and (for WFT methods) n -particle correlation treatment or (for DFT methods) exchange-correlation functional, for several representative partial charge definitions such as QTAIM, Hirshfeld, Hirshfeld-I, HLY (electrostatic), NPA, and GAPT. Our findings show that semi-empirical double hybrids can closely approach the CCSD(T) 'gold standard' for this property. In fact, owing to an error compensation in MP2, CCSD partial charges are further away from CCSD(T) than is MP2. The nonlocal correlation is important, especially when there is a substantial amount of nonlocal exchange. Employing range separation proves to be "mostly" not advantageous, while global hybrids perform optimally for 20%-30% Hartree-Fock exchange across all charge types. Basis set convergence analysis shows that an augmented triple-zeta heavy-aug-cc-pV(T+d)Z basis set or a partially augmented jun-cc-pV(T+d)Z basis set is sufficient for Hirshfeld, Hirshfeld-I, HLY, and GAPT charges. In contrast, QTAIM and NPA display slower basis set convergence. It is noteworthy that for both NPA and QTAIM, HF exhibits markedly slower basis set convergence than the correlation components of MP2 and CCSD. Triples corrections in CCSD(T), denoted as CCSD(T)-CCSD, exhibit even faster basis set convergence.

The tale of HORTON: Lessons learned in a decade of scientific software development

HORTON is a free and open-source electronic-structure package written primarily in Python 3 with some underlying C++ components. While HORTON's development has been mainly directed by the research interests of its leading contributing groups, it is designed to be easily modified, extended, and used by other developers of quantum chemistry methods or post-processing techniques. Most importantly, HORTON adheres to modern principles of software development, including modularity, readability, flexibility, comprehensive documentation, automatic testing, version control, and quality-assurance protocols. This article explains how the principles and structure of HORTON have evolved since we started developing it more than a decade ago. We review the features and functionality of the latest HORTON release (version 2.3) and discuss how HORTON is evolving to support electronic structure theory research for the next decade.

Structure and Ultrafast X-ray Diffraction of the Hydrated Metaphosphate

We study the pathway of metaphosphate hydration when a metaphosphate anion is dissolved in liquid water with an explicit water model. For this purpose, we propose a sequential Monte Carlo algorithm incorporated with the ab initio quantum mechanics/molecular mechanics (QM/MM) method, which can reduce the amount of ab initio QM/MM sampling while retaining the accuracy of the simulation. We demonstrate the numerical calculation of the standard enthalpy change for the successive addition reaction PO3-·2H2O + H2O ⇌ PO3-·3H2O in the liquid phase, which helps to clarify the hydration pathway of the metaphosphate. With the obtained hydrated structure of the metaphosphate anion, we perform ab initio calculations for its relaxation dynamics upon vibrational excitation and characterize the energy transfer process in solution with simulated ultrafast X-ray diffraction signals, which can be experimentally implemented with X-ray free-electron lasers.

PCMRESP: A Method for Polarizable Force Field Parameter Development and Transferability of the Polarizable Gaussian Multipole Models Across Multiple Solvents

The transferability of force field parameters is a crucial aspect of high-quality force fields. Previous investigations have affirmed the transferability of electrostatic parameters derived from polarizable Gaussian multipole models (pGMs) when applied to water oligomer clusters, polypeptides across various conformations, and different sequences. In this study, we introduce PCMRESP, a novel method for electrostatic parametrization in solution, intended for the development of polarizable force fields. We utilized this method to assess the transferability of three models: a fixed charge model and two variants of pGM models. Our analysis involved testing these models on 377 small molecules and 100 tetra-peptides in five representative dielectric environments: gas, diethyl ether, dichloroethane, acetone, and water. Our findings reveal that the inclusion of atomic polarization significantly enhances transferability and the incorporation of permanent atomic dipoles, in the form of covalent bond dipoles, leads to further improvements. Moreover, our tests on dual-solvent strategies demonstrate consistent transferability for all three models, underscoring the robustness of the dual-solvent approach. In contrast, an evaluation of the traditional HF/6-31G* method indicates poor transferability for the pGM-ind and pGM-perm models, suggesting the limitations of this conventional approach.

Atomic Charge Dependency of Spiropyran/Merocyanine Adsorption as a Precursor to Surface Isomerization Reactions

This computational study investigates the adsorption of various spiropyran and merocyanine isomers on a NaCl substrate using a combination of density functional theory (DFT) and molecular mechanics (MM) calculations. Four different charge methods were used to determine the partial atomic charges for the adsorbate molecules, including Mulliken population analysis and three electrostatic potential (ESP) methods (Merz-Kollman, ChelpG, and Hu-Lu-Yang), while three different force fields (AMBER 3, CHARMM 27, and MM+) were employed for the MM calculations. The results show that the various DFT charge methods produced similar outcomes for the molecules' partial atomic charges, with some exceptions for individual atoms and methods. Additionally, it was found that the ESP charge methods were more sensitive to the conformer orientation than the Mulliken approach. The adsorption behavior of merocyanine conformers with the central bond in trans orientation (T-conformers) was similar for various configurations, with the molecule adsorbing mostly flat with its aromatic rings almost parallel to the substrate. However, C-conformers (with their central bond in cis orientation) and spiropyran isomers exhibited inconsistent adsorption behavior, mostly because only some of the aromatic rings contributed to the adsorption behavior. Due to additional van der Waals interactions of more aromatic rings, the adsorption energies for T-conformers are consistently 0.2-0.3 eV higher than for C-conformers and for spiropyran. The study found that the adsorption geometries and energies of stable T-conformers were independent of the partial atomic charge scheme and force field used, and C-conformers show parameter-dependent behavior upon adsorption, leading to metastable configurations. These findings indicate viable pathways during the spiropyran-merocyanine isomerization reactions. Therefore, the results provide initial insights into the possibility of switching spiropyran isomers into merocyanine isomers and vice versa after adsorption onto substrates.

Streamlining and Optimizing Strategies of Electrostatic Parameterization

Accurate characterization of electrostatic interactions is crucial in molecular simulation. Various methods and programs have been developed to obtain electrostatic parameters for additive or polarizable models to replicate electrostatic properties obtained from experimental measurements or theoretical calculations. Electrostatic potentials (ESPs), a set of physically well-defined observables from quantum mechanical (QM) calculations, are well suited for optimization efforts due to the ease of collecting a large amount of conformation-dependent data. However, a reliable set of QM ESP computed at an appropriate level of theory and atomic basis set is necessary. In addition, despite the recent development of the PyRESP program for electrostatic parameterizations of induced dipole-polarizable models, the time-consuming and error-prone input file preparation process has limited the widespread use of these protocols. This work aims to comprehensively evaluate the quality of QM ESPs derived by eight methods, including wave function methods such as Hartree-Fock (HF), second-order Møller-Plesset (MP2), and coupled cluster-singles and doubles (CCSD), as well as five hybrid density functional theory (DFT) methods, used in conjunction with 13 different basis sets. The highest theory levels CCSD/aug-cc-pV5Z (a5z) and MP2/aug-cc-pV5Z (a5z) were selected as benchmark data over two homemade data sets. The results show that the hybrid DFT method, ωB97X-D, combined with the aug-cc-pVTZ (a3z) basis set, performs well in reproducing ESPs while taking both accuracy and efficiency into consideration. Moreover, a flexible and user-friendly program called PyRESP_GEN was developed to streamline input file preparation. The restraining strengths, along with strategies for polarizable Gaussian multipole (pGM) model parameterizations, were also optimized. These findings and the program presented in this work facilitate the development and application of induced dipole-polarizable models, such as pGM models, for molecular simulations of both chemical and biological significance.

Computational Framework Combining Quantum Mechanics, Molecular Dynamics, and Deep Neural Networks to Evaluate the Intrinsic Properties of Materials

The design and evaluation of future nanomaterials with specific properties is a challenging task as the current traditional methods rely on trial and error approaches that are time-consuming and expensive. On the computational front, design tools such as molecular dynamics (MD) simulations help us reduce the costs and times. However, nonbonded potential parameters, the key input parameters for an MD simulation, are usually not available for designing and studying new materials. Resolving this, quantum mechanics (QM) calculations could be used to evaluate the system's energy as a function of the nonbonded distances, and the resulting data set could be fit to a generic potential equation to obtain the fitting constants (potential parameters). However, fitting this massive data set containing thousands of unknown parameters using traditional mathematical formulations is not feasible. Hence, most computational frameworks in the literature utilize several simplifications, leading to a severe loss of accuracy. Addressing this deficiency, in this work, we propose a multi-scale framework that couples QM calculations and MD with advanced deep neural networks to determine the potential parameters. This advanced framework has been extensively validated by employing it to predict properties such as the density, boiling point, and melting point of five different types of molecules that are well-understood, namely, the polar molecule H2O, ionic compound LiPF6, ethanol (C2H5OH), long-chain molecule C8H18, and the complex molecular system ethylene carbonate (EC).

Atomic charges in molecules defined by molecular real space partition into atomic subspaces

Atomic charge (AC), which is the charge distribution of a molecule, is an important property that is closely associated with structures, reactivities, and intra- and inter-molecular interactions among molecules. Several theoretical models or methods can be used to obtain the magnitudes of AC with different characteristics. These models can be classified into fuzzy-atoms models and models partitioning a molecule into individual atoms with sharp boundaries. The first category includes Mulliken, natural population analysis (NPA), Hirshfeld, Merz-Kollman-Singh (MK), CHELPG, the electronegativity equalization method (EEM), the atom-bond electronegativity equalization method (ABEEM), and atomic polar tensor (APT). The second category is derived from quantum chemical topology (QCT) and includes the quantum theory of atoms in molecules (QTAIM) and QCT analysis based on the potential acting on one electron in a molecule (PAEMQCT). Herein, after giving a bird's-eye view of the population methods of the first category, we specifically describe some features of the second category. We only present the basic framework of QCT for obtaining ACs from QTAIM and PAEMQCT and show their important characteristics. QCT establishes the basis of the following chemical concept: a molecule is spatially partitioned into individual atoms with sharp boundaries. The ACs from QTAIM are close to the atomic valence in chemistry, and ACs from PAEMQCT may be practically suitable for modeling intra- and inter-molecular interactions.

Lennard-Jones interaction parameters of Mo and W in He and N2 from collision cross-sections of Lindqvist and Keggin polyoxometalate anions

Drift tube ion mobility spectrometry (DTIMS) coupled with mass spectrometry was used to determine the collision cross-sections (^DTCCS) of polyoxometalate anions in helium and nitrogen. As the geometry of the ion, more than its mass, determines the collision cross-section with a given drift gas molecule, we found that both Lindqvist ions Mo₆O₁₉^2- and W₆O₁₉^2- had a ^DTCCS_He value of 103 ± 2 Ų, and both Keggin ions PMo₁₂O₄₀^3- and PW₁₂O₄₀^3- had a ^DTCCS_He value of 170 ± 2 Ų. Similarly, ion mobility experiments in N₂ led to ^DTCCS_N2 values of 223 ± 2 Ų and 339 ± 4 Ų for Lindqvist and Keggin anions, respectively. Using optimized structures and partial charges determined from density functional theory calculations, followed by CCS calculations via the trajectory method, we determined Lennard-Jones 6-12 potential parameters ε, σ of 5.60 meV, 3.50 Å and 3.75 meV, 4.40 Å for both Mo and W atoms interacting with He and N₂, respectively. These parameters reproduced the CCS of polyoxometalates within 2% accuracy.

Evaluation of OH Radical Reaction Positions in 3-Ring PAHs Using Transition State Energy and Atomic Charge Calculations

In this study, transition state energy and atomic charge were calculated using the Gaussian 09 program with focus on three-ring PAHs, such as acenaphthylene and anthracene, which are most likely found in contaminated sites. The calculation results were then compared with the radical reaction positions reported in the existing literature. Because the energy difference between the reactant and the transition state according to the reaction position was very small, no distinct correlation was obtained when results were compared with those of the OH radical test findings reported in the literature. It was also found that the charge calculation makes it possible to accurately predict the radical reaction position of the target material. In addition, MK and HLY charges were found to be more accurate than CHelpG charges in predicting the radical reaction positions. The charge calculation can also be applied in predicting radical reaction positions for hazardous materials with different molecular structures.

Free-Energy Profile Analysis of the Catalytic Reaction of Glycinamide Ribonucleotide Synthetase

The second step in the de novo biosynthetic pathway of purine is catalyzed by PurD, which consumes an ATP molecule to produce glycinamide ribonucleotide (GAR) from glycine and phosphoribosylamine (PRA). PurD initially reacts with ATP to produce an intermediate, glycyl-phosphate, which then reacts with PRA to produce GAR. The structure of the glycyl-phosphate intermediate bound to PurD has not been determined. Therefore, the detailed reaction mechanism at the molecular level is unclear. Here, we developed a computational protocol to analyze the free-energy profile for the glycine phosphorylation process catalyzed by PurD, which examines the free-energy change along a minimum energy path based on a perturbation method combined with the quantum mechanics and molecular mechanics hybrid model. Further analysis revealed that during the formation of glycyl-phosphate, the partial atomic charge distribution within the substrate molecules was not localized according to the formal charges, but was delocalized overall, which contributed significantly to the interaction with the charged amino acid residues in the ATP-grasp domain of PurD.

Apples to apples comparison of standardized to unstandardized principal component analysis of methods that assign partial atomic charges in molecules

Articles by Cho et al. (ChemPhysChem, 2020, 21, 688–696) and Manz (RSC Adv., 2020, 10, 44121–44148) performed unstandardized and standardized, respectively, principal component analysis (PCA) to study atomic charge assignment methods for molecular systems. Both articles used subsets of atomic charges computed by Cho et al.; however, the data subsets employed were not strictly identical. Herein, an element by element analysis of this dataset is first performed to compare the spread of charge values across individual chemical elements and charge assignment methods. This reveals an underlying problem with the reported Becke partial atomic charges in this dataset. Due to their unphysical values, these Becke charges were not included in the subsequent PCA. Standardized and unstandardized PCA are performed across two datasets: (i) 19 charge assignment methods having a complete basis set limit and (ii) all 25 charge assignment methods (excluding Becke) for which Cho et al. computed atomic charges. The dataset contained ∼2000 molecules having a total of 29 907 atoms in materials. The following five methods (listed here in alphabetical order) showed the greatest correlation to the first principal component in standardized and unstandardized PCA: DDEC6, Hirshfeld-I, ISA, MBIS, and MBSBickelhaupt (note: MBSBickelhaupt does not appear in the 19 methods dataset). For standardized PCA, the DDEC6 method ranked first followed closely by MBIS. For unstandardized PCA, Hirshfeld-I (19 methods) or MBSBickelhaupt (25 methods) ranked first followed by DDEC6 in second place (both 19 and 25 methods).

Standardized and unstandardized principal component analyses are directly compared for a dataset of ∼2000 molecules across various charge assignment methods.

Combining machine learning and quantum mechanics yields more chemically aware molecular descriptors for medicinal chemistry applications

Molecular interaction fields (MIFs), describing molecules in terms of their ability to interact with any chemical entity, are one of the most established and versatile concepts in drug discovery. Improvement of this molecular description is highly desirable for in silico drug discovery and medicinal chemistry applications. In this work, we revised a well‐established molecular mechanics' force field and applied a hybrid quantum mechanics and machine learning approach to parametrize the hydrogen‐bonding (HB) potentials of small molecules, improving this aspect of the molecular description. Approximately 66,000 molecules were chosen from available drug databases and subjected to density functional theory calculations (DFT). For each atom, the molecular electrostatic potential (EP) was extracted and used to derive new HB energy contributions; this was subsequently combined with a fingerprint‐based description of the structural environment via partial least squares modeling, enabling the new potentials to be used for molecules outside of the training set. We demonstrate that parameter prediction for molecules outside of the training set correlates with their DFT‐derived EP, and that there is correlation of the new potentials with hydrogen‐bond acidity and basicity scales. We show the newly derived MIFs vary in strength for various ring substitution in accordance with chemical intuition. Finally, we report that this derived parameter, when extended to non‐HB atoms, can also be used to estimate sites of reaction.

Accurate Modeling of Excitonic Coupling in Cyanine Dye Cy3

Accurate modeling of excitonic coupling in molecules is of great importance for inferring the structures and dynamics of coupled systems. Cy3 is a cyanine dye that is widely used in molecular spectroscopy. Its well-separated excitation bands, high sensitivity to the surroundings, and the high energy transfer efficiency make it a perfect choice for excitonic coupling experiments. Many methods have been used to model the excitonic coupling in molecules with varying degrees of accuracy. The atomic transition charge model offers a high-accuracy and cost-effective way to calculating the excitonic coupling. The main focus of this work is to generate high-quality atomic transition charges that can accurately model the Cy3 dye's transition density. The transition density of the excitation of the ground to first excited state is calculated using configuration-interaction singles and time-dependent density functional theory and is benchmarked against the algebraic diagrammatic construction method. Using the transition density we derived the atomic transition charges using two approaches: Mulliken population analysis and charges fitted to the transition electrostatic potential. The quality of the charges is examined, and their ability to accurately calculate the excitonic coupling is assessed via comparison to experimental data of an artificial biscyanine construct. Theoretical comparisons to the supermolecule ab initio couplings and the widely used point-dipole approximation are also made. Results show that using the transition electrostatic potential is a reliable approach for generating the transition atomic charges. A high-quality set of charges, that can be used to model the Cy3 dye dimer excitonic coupling with high-accuracy and a reasonable computational cost, is obtained.

Crystal Structure Prediction Methods for Organic Molecules: State of the Art

The prediction of the crystal structures that a given organic molecule is likely to form is an important theoretical problem of significant interest for the pharmaceutical and agrochemical industries, among others. As evidenced by a series of six blind tests organized over the past 2 decades, methodologies for crystal structure prediction (CSP) have witnessed substantial progress and have now reached a stage of development where they can begin to be applied to systems of practical significance. This article reviews the state of the art in general-purpose methodologies for CSP, placing them within a common framework that highlights both their similarities and their differences. The review discusses specific areas that constitute the main focus of current research efforts toward improving the reliability and widening applicability of these methodologies, and offers some perspectives for the evolution of this technology over the next decade.

Non long-range corrected density functionals incorrectly describe the intensity of the CH stretching band in polycyclic aromatic hydrocarbons

We present a comprehensive study of the most relevant numerical aspects influencing frequencies and intensities in the infrared spectrum of isolated polycyclic aromatic hydrocarbons (PAHs) regarding the overestimate of the IR CH-stretching bands. We use naphthalene as benchmark and show the validity of our results to different members of the PAH family. Our analysis relies on widely employed density functional theory methods and second-order vibrational perturbational theory for the computation of vibrational eigenstates. We have focused on the elucidation of the origin of the systematic overestimate of the intensities in the CH-stretching region. To rule out nonfundamental numerical errors, we have initially considered the influence of the electronic basis set and various other parameters on the different stages of the vibrational analysis. In a second stage, we have benchmarked the results of different density functional theory functionals with respect to the aforementioned overestimate taken as the ratio between the most prominent features of the spectrum, the CH-bending and the CH-stretching bands. Our results unambiguously indicate that the long-range correction plays a major role in this spurious numerical issue. More specifically, this phenomenon is due to an incorrect description of the charge distribution (and hence dipole) within the symmetrically relevant CH bonds. Long-range correction specifically remedies this issue. It improves the description of the intensities in the stretching region while at the same time it does not perturb significantly the rest of the spectrum. With respect to the frequencies, we have observed an overall improvement when compared to noncorrected functionals.

Determining Partial Atomic Charges for Liquid Water: Assessing Electronic Structure and Charge Models

Partial atomic charges provide an intuitive and efficient way to describe the charge distribution and the resulting intermolecular electrostatic interactions in liquid water. Many charge models exist and it is unclear which model provides the best assignment of partial atomic charges in response to the local molecular environment. In this work, we systematically scrutinize various electronic structure methods and charge models (Mulliken, natural population analysis, CHelpG, RESP, Hirshfeld, Iterative Hirshfeld, and Bader) by evaluating their performance in predicting the dipole moments of isolated water, water clusters, and liquid water as well as charge transfer in the water dimer and liquid water. Although none of the seven charge models is capable of fully capturing the dipole moment increase from isolated water (1.85 D) to liquid water (about 2.9 D), the Iterative Hirshfeld method performs best for liquid water, reproducing its experimental average molecular dipole moment, yielding a reasonable amount of intermolecular charge transfer, and showing modest sensitivity to the local water environment. The performance of the charge model is dependent on the choice of the density functional and the quantum treatment of the environment. The computed molecular dipole moment of water generally increases with the percentage of the exact Hartree-Fock exchange in the functional, whereas the amount of charge transfer between molecules decreases. For liquid water, including two full solvation shells of surrounding water molecules (within about 5.5 Å of the central water) in the quantum chemical calculation converges the charges of the central water molecule. Our final pragmatic quantum chemical charge-assigning protocol for liquid water is the Iterative Hirshfeld method with M06-HF/aug-cc-pVDZ and a quantum region cutoff radius of 5.5 Å.

Analysis and visualization of energy densities. II. Insights from linear-response time-dependent density functional theory calculations

Inspired by the analysis of Kohn-Sham energy densities by Nakai and coworkers, we extended the energy density analysis to linear-response time-dependent density functional theory (LR-TDDFT) calculations. Using ethylene-tetrafluoroethylene and oxyluciferin-water complexes as examples, distinctive distribution patterns were demonstrated for the excitation energy densities of local excitations (within a molecular fragment) and charge-transfer excitations (between molecular fragments). It also provided a simple way to compute the effective energy of both hot carriers (particle and hole) from charge-transfer excitations via an integration of the excitation energy density over the donor and acceptor grid points.

Charge distributions for molecular dynamics simulations from self-consistent polarization method

Partial atomic charges are important force field parameters. They are usually computed by applying quantum-chemical calculations and the assumed population scheme. In this study polarization consistent scheme of deriving a charge distribution inside solute molecule is proposed. The environment effect is explicitly taken into account by distributing solvent molecules around the solute target. The performed analysis includes a few computational schemes (HF, MP2, B3LYP, and M026X), basis sets (cc-pvnz, n = 2, 3, …, 6), and electrostatically derived charge distributions (KS, CHELP, CHELPG, and HLY). It is demonstrated that the environment effect is very important and cannot be disregarded. The second solvation shell should be included to achieve the charge convergence. Huge corrections to charge distribution are due to induction and dispersion. The B3LYP/cc-pvqz level of theory is recommended for deriving the charges within self-consistent polarization scheme.

Tackling Solvent Effects by Coupling Electronic and Molecular Density Functional Theory

Solvation effects can have a tremendous influence on chemical reactions. However, precise quantum chemistry calculations are most often done either in vacuum neglecting the role of the solvent or using continuum solvent model ignoring its molecular nature. We propose a new method coupling a quantum description of the solute using electronic density functional theory with a classical grand-canonical treatment of the solvent using molecular density functional theory. Unlike a previous work, both densities are minimized self-consistently, accounting for mutual polarization of the molecular solvent and the solute. The electrostatic interaction is accounted using the full electron density of the solute rather than fitted point charges. The introduced methodology represents a good compromise between the two main strategies to tackle solvation effects in quantum calculation. It is computationally more effective than a direct quantum mechanics/molecular mechanics coupling, requiring the exploration of many solvent configurations. Compared to continuum methods, it retains the full molecular-level description of the solvent. We validate this new framework onto two usual benchmark systems: a water solvated in water and the symmetrical nucleophilic substitution between chloromethane and chloride in water. The prediction for the free energy profiles are not yet fully quantitative compared to experimental data, but the most important features are qualitatively recovered. The method provides a detailed molecular picture of the evolution of the solvent structure along the reaction pathway.

Energy, orbital and structural stacking landscape of a purine homodimer system

The multidimensional study, combining the extensive calculations of potential energy surfaces for the parallel-displaced configurations and methods such as energy decomposition and natural bond orbital analysis, has been carried out. The resulted data give an energy, orbital and structural landscapes of this biologically essential system. The balance of the two energy sources, electrostatic and dispersion, is clearly visible. The obtained results, taken as a whole, provide an insight into the hierarchy of intermolecular interactions in the purine system, together with their sources.

1,4-Dideoxy-1,4-imino-d-arabinitol (DAB) Analogues Possessing a Hydrazide Imide Moiety as Potent and Selective α-Mannosidase Inhibitors

The synthesis of two polyhydroxylated pyrrolidines as 1,4-dideoxy-1,4-imino-d-arabinitol (DAB) analogues bearing a hydrazide moiety is described. The DAB analogues act as selective and potent inhibitors of α-mannosidase in the submicromolar concentration ranges (K _i values ranging from 0.23 to 1.4 μM).

The Atomic Partial Charges Arboretum: Trying to See the Forest for the Trees

Atomic partial charges are among the most commonly used interpretive tools in quantum chemistry. Dozens of different 'population analyses' are in use, which are best seen as proxies (indirect gauges) rather than measurements of a 'general ionicity'. For the GMTKN55 benchmark of nearly 2,500 main-group molecules, which span a broad swathe of chemical space, some two dozen different charge distributions were evaluated at the PBE0 level near the 1-particle basis set limit. The correlation matrix between the different charge distributions exhibits a block structure; blocking is, broadly speaking, by charge distribution class. A principal component analysis on the entire dataset suggests that nearly all variation can be accounted for by just two 'principal components of ionicity': one has all the distributions going in sync, while the second corresponds mainly to Bader QTAIM vs. all others. A weaker third component corresponds to electrostatic charge models in opposition to the orbital-based ones. The single charge distributions that have the greatest statistical similarity to the first principal component are iterated Hirshfeld (Hirshfeld-I) and a minimal-basis projected modification of Bickelhaupt charges. If three individual variables, rather than three principal components, are to be identified that contain most of the information in the whole dataset, one representative for each of the three classes of Corminboeuf et al. is needed: one based on partitioning of the density (such as QTAIM), a second based on orbital partitioning (such as NPA), and a third based on the molecular electrostatic potential (such as HLY or CHELPG).

Model systems for screening and investigation of lithium metal electrode chemistry and dendrite formation

The use of lithium metal as an electrode for electrochemical energy storage will provide a significant impact on practical energy storage technology. Unfortunately, the use of lithium metal is plagued with challenging chemical problems. Specifically, the formation of a solid electrolyte interphase layer and the nucleation and growth of lithium dendrites: both must be addressed and controlled in order to achieve a practically useable pure lithium metal electrode. Currently sophisticated experimental techniques and computationally expensive simulations are being used to probe these problems but these methods are arduous and time consuming which delays timely evaluation and insight into the rapidly changing field of advanced energy storage. Here, we report the use of DFT simulations of lithium nanoclusters to investigate and explore lithium metal chemistry with inexpensive computational methods to gain greater insight into electrochemical reductions and the nucleation and growth of dendrites. DME, LiTFSI, and LiFSI reduction energetics and structures with electrode effects from lithium metal are reported providing better physical description of the absolute reduction potential characterization. The electronic structure of the lithium nanoclusters were used to investigate the nucleation and growth of lithium dendrites from an ab initio perspective. The results demonstrate that kinetic processes have more control over non uniform growth than thermodynamic processes. Based on this information, a non ab initio model was created in Matlab that shows the initial stages of dendrite nucleation considering approximately 2000 atoms.

Seven confluence principles: a case study of standardized statistical analysis for 26 methods that assign net atomic charges in molecules

This article studies two kinds of information extracted from statistical correlations between methods for assigning net atomic charges (NACs) in molecules. First, relative charge transfer magnitudes are quantified by performing instant least squares fitting (ILSF) on the NACs reported by Cho et al. (ChemPhysChem, 2020, 21, 688–696) across 26 methods applied to ∼2000 molecules. The Hirshfeld and Voronoi deformation density (VDD) methods had the smallest charge transfer magnitudes, while the quantum theory of atoms in molecules (QTAIM) method had the largest charge transfer magnitude. Methods optimized to reproduce the molecular dipole moment (e.g., ACP, ADCH, CM5) have smaller charge transfer magnitudes than methods optimized to reproduce the molecular electrostatic potential (e.g., CHELPG, HLY, MK, RESP). Several methods had charge transfer magnitudes even larger than the electrostatic potential fitting group. Second, confluence between different charge assignment methods is quantified to identify which charge assignment method produces the best NAC values for predicting via linear correlations the results of 20 charge assignment methods having a complete basis set limit across the dataset of ∼2000 molecules. The DDEC6 NACs were the best such predictor of the entire dataset. Seven confluence principles are introduced explaining why confluent quantitative descriptors offer predictive advantages for modeling a broad range of physical properties and target applications. These confluence principles can be applied in various fields of scientific inquiry. A theory is derived showing confluence is better revealed by standardized statistical analysis (e.g., principal components analysis of the correlation matrix and standardized reversible linear regression) than by unstandardized statistical analysis. These confluence principles were used together with other key principles and the scientific method to make assigning atom-in-material properties non-arbitrary. The N@C₆₀ system provides an unambiguous and non-arbitrary falsifiable test of atomic population analysis methods. The HLY, ISA, MK, and RESP methods failed for this material.

Standardized statistical analysis of many methods to assign net atomic charges revealed relative charge transfer magnitudes and confluent correlations.

Computational Evidence Suggests That 1-Chloroethanol May Be an Intermediate in the Thermal Decomposition of 2-Chloroethanol into Acetaldehyde and HCl

The dehalogenation of 2-chloroethanol (2ClEtOH) in the gas phase with and without the participation of catalytic water molecules has been investigated using methods rooted into the density functional theory. The well-known HCl elimination leading to vinyl alcohol (VA) was compared to the alternative elimination route toward oxirane and shown to be kinetically and thermodynamically more favorable. However, the isomerization of VA to acetaldehyde in the gas phase, in the absence of water, was shown to be kinetically and thermodynamically less favorable than the recombination of VA and HCl to form the isomeric 1-chloroethanol (1ClEtOH) species. At the ωB97X-D/cc-pVTZ level of calculation, this species is more stable than 2ClEtOH by about 6 kcal mol^-1 at 298 K, and the reaction barrier for VA to 1ClEtOH is 23 kcal mol^-1 versus 55 kcal mol^-1 for the direct transformation of VA to acetaldehyde. In a successive step, 1ClEtOH can decompose directly to acetaldehyde and HCl with a lower barrier (29 kcal mol^-1) than that of VA to the same products (55 kcal mol^-1). The calculations were repeated using a single ancillary water molecule (W) in the complexes 2ClEtOH_W and 1ClEtOH_W. The latter adduct is now more stable than 2ClEtOH_W by about 8 kcal mol^-1 at 298 K, implying that the water molecule increased the already higher stability of 1ClEtOH in the gas phase. However, this catalytic water molecule lowers dramatically the barrier for the interconversion of VA to acetaldehyde (from 55 to 7 kcal mol^-1). This barrier is now smaller than the one for the conversion to 1ClEtOH (which also decreases, but not so much, from 23 to 13 kcal mol^-1). Thus, it is concluded that while 1ClEtOH may be a plausible intermediate in the gas phase dehalogenation of 2ClEtOH, it is unlikely that it plays a major role in water complexes (or, by inference, aqueous solution). It is also shown that neither in the gas phase nor in the cluster with one water molecule, the oxirane path is more favorable than the VA alcohol path. Additionally, a direct conversion of 2ClEtOH to 1ClEtOH through a transition state which resembles a VA molecule in a complex with a chlorine atom and a hydrogen atom on both sides of this planar species was found. This reaction path has also lower activation energy than the conversion to oxirane but not as low as the conversion to VA.

Synthesis of α-Fluoro-α-Amino Acid Derivatives via Photoredox-Catalyzed Carbofluorination

A mild, metal-free, regioselective carbofluorination of dehydroalanine derivatives has been developed. Alkyl radicals resulting from visible-light photoredox catalysis engage in a radical conjugate addition to dehydroalanine, with subsequent fluorination of the newly generated radical to afford an α-fluoro-α-amino acid. By using a highly oxidizing organic photocatalyst, this process incorporates non-stabilized primary, secondary, and tertiary alkyl radicals derived from commercially available alkyltrifluoroborates to furnish a wide range of fluorinated unnatural amino acids.

A Density Functional Tight Binding Layer for Deep Learning of Chemical Hamiltonians

Current neural networks for predictions of molecular properties use quantum chemistry only as a source of training data. This paper explores models that use quantum chemistry as an integral part of the prediction process. This is done by implementing self-consistent-charge Density-Functional-Tight-Binding (DFTB) theory as a layer for use in deep learning models. The DFTB layer takes, as input, Hamiltonian matrix elements generated from earlier layers and produces, as output, electronic properties from self-consistent field solutions of the corresponding DFTB Hamiltonian. Backpropagation enables efficient training of the model to target electronic properties. Two types of input to the DFTB layer are explored, splines and feed-forward neural networks. Because overfitting can cause models trained on smaller molecules to perform poorly on larger molecules, regularizations are applied that penalize nonmonotonic behavior and deviation of the Hamiltonian matrix elements from those of the published DFTB model used to initialize the model. The approach is evaluated on 15 700 hydrocarbons by comparing the root-mean-square error in energy and dipole moment, on test molecules with eight heavy atoms, to the error from the initial DFTB model. When trained on molecules with up to seven heavy atoms, the spline model reduces the test error in energy by 60% and in dipole moments by 42%. The neural network model performs somewhat better, with error reductions of 67% and 59%, respectively. Training on molecules with up to four heavy atoms reduces performance, with both the spline and neural net models reducing the test error in energy by about 53% and in dipole by about 25%.

Protonation and water exchange kinetics in sandwich polyoxometalates

Density functional theory is used to explore the locus and consequences of protonation in [Zn4(HO)2(PW9O34)2]10-. The results are used to explain recent observations regarding the contrasting pH effects on the water-ligand exchange in [Mn4(H2O)2(P2W15O56)2]16- and [Co4(H2O)2(P2W15O56)2]16-, and the general effect of protonation on solvent exchange in metal oxides is discussed.

Representation of the QM Subsystem for Long-Range Electrostatic Interaction in Non-Periodic Ab Initio QM/MM Calculations

In QM/MM calculations, it is essential to handle electrostatic interactions between the QM and MM subsystems accurately and efficiently. To achieve maximal efficiency, it is convenient to adopt a hybrid scheme, where the QM electron density is used explicitly in the evaluation of short-range QM/MM electrostatic interactions, while a multipolar representation for the QM electron density is employed to account for the long-range QM/MM electrostatic interactions. In order to avoid energy discontinuity at the cutoffs, which separate the short- and long-range QM/MM electrostatic interactions, a switching function should be utilized to ensure a smooth potential energy surface. In this study, we benchmarked the accuracy of such hybrid embedding schemes for QM/MM electrostatic interactions using different multipolar representations, switching functions and cutoff distances. For test systems (neutral and anionic oxyluciferin in MM (aqueous and enzyme) environments), the best accuracy was acquired with a combination of QM electrostatic potential (ESP) charges and dipoles and two switching functions (long-range electrostatic corrections (LREC) and Switch) in the treatment of long-range QM/MM electrostatics. It allowed us to apply a 10Å distance cutoff and still obtain QM/MM electrostatics/polarization energies within 0.1 kcal/mol and time-dependent density functional theory (TDDFT)/MM vertical excitation energies within 10-3 eV from theoretical reference values.

Evaluating the Effects of Geometry and Charge Flux in Force Field Modeling

We apply a model for analyzing the importance of conformational charge flux to 11 molecules with the R-(CH₂) _n-R structure (R = Cl, F, OH, SH, COOH, CONH₂, and NH₂ and n = 4-6). Atomic charges were obtained by fitting to results from density functional theory calculations using the HLY procedure, and their geometry dependence is decomposed into contributions from changes in bond lengths, bond angles, and torsional angles. The torsional degrees of freedom are the main contribution to the conformational dependence of atomic charges and molecular dipole moments, but indirect effects due to changes in bond distances and angles account for ∼15% of the variations. While the magnitude of charge flux and geometry effects have been found to be independent of the number of internal degrees of freedom, the nature of the R- group has a moderate influence. The indirect effects are comparable for all of the R-groups and are approximately one-half the magnitude of the corresponding effects in peptide models. However, the magnitudes are different, yet the relative importance of geometry and charge flux effects are completely similar to those of the peptide models, which suggests that modeling the charge flux effects for changes in bond lengths, bond angles, and torsional angles should be considered for developing improved force fields.

Development of CHARMM-Compatible Force-Field Parameters for Cobalamin and Related Cofactors from Quantum Mechanical Calculations

Corrinoid cofactors such as cobalamin are used by many enzymes and are essential for most living organisms. Therefore, there is broad interest in investigating cobalamin-protein interactions with molecular dynamics simulations. Previously developed parameters for cobalamins are based mainly on crystal structure data. Here, we report CHARMM-compatible force field parameters for several corrinoids developed from quantum mechanical calculations. We provide parameters for corrinoids in three oxidation states, Co³⁺, Co²⁺, and Co¹⁺, and with various axial ligands. Lennard-Jones parameters for the cobalt center in the Co(II) and Co(I) states were optimized using a helium atom probe, and partial atomic charges were obtained with a combination of natural population analysis (NPA) and restrained electrostatic potential (RESP) fitting approaches. The Force Field Toolkit was used to optimize all bonded terms. The resulting parameters, determined solely from calculations of cobalamin alone or in water, were then validated by assessing their agreement with density functional theory geometries and by analyzing molecular dynamics simulation trajectories of several corrinoid proteins for which X-ray crystal structures are available. In each case, we obtained excellent agreement with the reference data. In comparison to previous CHARMM-compatible parameters for cobalamin, we observe a better agreement for the fold angle and lower RMSD in the cobalamin binding site. The approach described here is readily adaptable for developing CHARMM-compatible force-field parameters for other corrinoids or large biomolecules.

Coarse-Grained Molecular Dynamics Force-Field for Polyacrylamide in Infinite Dilution Derived from Iterative Boltzmann Inversion and MARTINI Force-Field

We present a mesoscale model of aqueous polyacrylamide in the infinitely dilute concentration regime, by combining an extant coarse-grained (CG) force-field, MARTINI, and the Iterative Boltzmann Inversion protocol (IBI). MARTINI force-field was used to retain the thermodynamics of solvation of the polymer in water, whereas the structural properties and intrapolymer interactions were optimized by IBI. Atomistic molecular dynamics simulations of polymer in water were performed to benchmark the mesoscale simulations. Our results from the CG model show excellent agreement in structure with the atomistic system. We also studied the dynamical behavior of our CG system by computing the shear viscosity and compared it with the standard IBI model. The viscosity trends of our model were similar to the atomistic system, whereas the standard IBI model was highly dissimilar as expected. In summary, our hybrid CG model sufficiently mimics an infinitely dilute system, and is superior to both MARTINI and IBI in representing the structure and thermodynamics of the atomistic system, respectively. Our hybrid coarse-graining strategy promises applicability in large-scale simulations of polymeric/biological systems where the structure needs to be replicated accurately while preserving the thermodynamics of a smoother surrounding.

Discovering the stacking landscape of a pyridine-pyridine system

Extremely extensive calculations of potential energy surfaces for the parallel-displaced configuration of pyridine dimer systems have been carried out using a dispersion-corrected density functional. Instead of focusing on stationary geometries these calculations provide much deeper insight into the "landscape" of the interaction energies of the particular systems-one can learn how the pyridine dimer stability changes along with various geometrical parameters. Other calculations such as natural bond orbital and energy decomposition have also been applied. The interplay of two significant factors, electrostatic forces and electron correlation effects, have been evaluated. The role of π···π interactions in the stacked pyridine systems has also been confirmed, and surprisingly, this happened to be true even for the geometries where the formation of C-H···π interactions might be proposed instead. The combination of many different methods has revealed the complexity of the stacking interactions. Apart from providing a "literal new look" into pyridine interaction patterns another picture has emerged. A stacking interaction in a pyridine dimer system is perceived as a combination of many different sources of the interaction energy, including orbital ones, and this is true for many different geometries.