Molecular Geometry Optimization Research Articles

Analytical Evaluation of Ground State Gradients in Quantum Electrodynamics Coupled Cluster Theory.

Analytical gradients of potential energy surfaces play a central role in quantum chemistry, allowing for molecular geometry optimizations and molecular dynamics simulations. In strong coupling conditions, potential energy surfaces can account for strong interactions between matter and the quantized electromagnetic field. In this paper, we derive expressions for the ground state analytical gradients in quantum electrodynamics coupled cluster theory. We also present a Cholesky-based implementation for the coupled cluster singles and doubles model. We report timings to show the performance of the implementation and present optimized geometries to highlight cavity-induced molecular orientation effects in strong coupling conditions.

Semi-empirical supported, Ab initio derived thermodynamic properties for ClO2 and its sub and extended species, applied in water treatment cycles

This paper describes a group of sixty (60) sub and extended chlorine oxide species with the general formulae of ClxOy (with x ≤ 2, y ≤ 8). Their role in water treatment cycles, behaving as key reactive species, is represented by a complex sequence of chemical inter-dependencies, exposed as a cohesive set of chemical reactions to demonstrate their cyclic role in aqueous media. An empirical/semi-empirical computational approach, supported by Ab Initio simulations, in accordance with open-shell character, has been followed to determine their optimum molecular geometries, to obtain their thermochemical properties. Besides a single molecular analysis, Grand Canonical Ensemble simulations, supported by a revised library of force field parameters, constituted a core component of the computational approach and proved to be invaluable in confirming thermochemical properties. This approach also offered finite estimates of optimum model sizes, a benefit with wider modelling application. Extended molecular species of ClO2 display a complex sequence of bonding character, with a variable charge dissipation (reported as partial charges), which complicates selection of basis sets in optimizing molecular geometries, during Ab Initio analyses.Optimum molecular geometries were obtained using Gaussian and MOPAC, which in turn resulted in reliable Heats of Formation. These correlated well with energies extracted from the open literature. Thermodynamic Analysis of the reaction of selected chlorine oxides with water using FactSage, predicted the production of known and two previously undetected chlorine species, [ClO4]- and [ClOH2]+.

In Silico Investigation of Molecular Properties and Molecular Docking of Darunavir: An Anti‐HIV Drug

AbstractA second‐generation HIV protease enzyme inhibitor, darunavir is used in combination therapy for patients with history of prior antiretroviral treatments. It inhibits the cleavage of HIV encoded gag‐pol polyprotein in cells contaminated by a virus and thereby hinders the development of mature and infectious new virions. In this paper, optimization of molecular geometry of darunavir has been obtained by Density Functional Theory based B3LYP and ωB97XD methods with 6–311+G(d,p) basis set. The electro‐optical, global reactivity descriptors, and UV–visible spectrum of the drug have been examined using both the functionals. Further, binding affinity of darunavir at different sites of protein receptor (PDB ID: 5b18) has been analyzed using molecular docking technique. Results have been used to discuss electro‐optical and electronic properties of the drug along with its binding affinities with protein receptors.

Structure Elucidation and Computational Studies of the Thiazole Derivative Against SARS-CoV-2 Virus: Insights from XRD, DFT, Molecular Docking, and Molecular Dynamics Simulation

The present work is focused on the crystal structure, Hirshfeld surface, Density Functional Theory (DFT) studies of thiazole derivative N-benzyl-4-(4-bromophenyl)thaiazole-2-carboxamide (TT4). The crystal structure has been determined using single crystal X-ray diffraction analysis, which shows that the compound crystallizes in the monoclinic crystal system with space group P21/c. C-H⋯O type of hydrogen bond interaction is responsible for the crystal packing in crystal The molecular geometry optimization was performed by DFT calculations. The 2D scattered plot was generated by Reduced Density Gradient (RDG) analysis, which divulge the weak and noncovalent interactions in the compound TT4. In silico studies were carried out to delve into the binding pattern of the TT4 compound against SARS-CoV-2 proteins using molecular docking and molecular dynamics simulation. Finally, the binding free energy and the contributed energies were derived using MM-GBSA approach. The 7K40-ligand complex showed the highest binding free energy, and among all other interactions, the contributions of the covalent binding and van der Waals energy were found to be significant.

Study on low-rank coal flotation collector screening and performance based on molecular polarity index.

Extensive studies using a trial-and-error approach have been conducted on low-rank coal flotation collectors. However, screening efficient collectors remains a considerable challenge due to the lack of suitable screening principles. It has proven that polar compounds such as carboxylic acids and esters are effective collectors for low-rank coal flotation. In this work, the effects of carboxylic acid, alcohol, and methyl ester on the floatability of low-rank coal were compared, the flotation performance of the polar collector was evaluated with theoretical calculations, a suitable evaluation parameter was determined and a screening principle based on this parameter was determined. The results show that the enhancement effects of polar collectors on low-rank coal floatability follow the order of methyl decanoate > methyl laurate > methyl octanoate > sec-octanol > methyl oleate (or methyl oleate > sec-octanol) > n-octanoic acid. Compared with the molecular polarity index, the hydrophobicity indices log P and dipole moment cannot be used to accurately evaluate different types of collectors and the same type of collectors, respectively. At room temperature, liquid polar compounds with molecular polarity indices in the range of 6.0 ~ 8.0kcal/mol effectively enhance the floatability of low-rank coal. The molecular polarity index of the collector is used for the first time to screen effective collectors of low-rank coal in this work. This parameter is anticipated to be highly important for the development and research of low-rank coal and other mineral collectors. To obtain reasonable and accurate molecular structure, geometry optimization and frequency calculations of the studied collectors were conducted via the Gaussian 09 software package based on density functional theory at the B3LYP/6-311 + G (d, p) level. The integral equation formalism for the polarizable continuum model (IEF-PCM) was utilized with water as the solvent (dielectric constant = 78.36, T = 298K) for all the calculations. Then, the atomic charge distributions (MPA and NPA) and electrostatic potential maps, the dipole moment and molecular polarity index, and the log P and water solubilities of studied collectors were shown or calculated by Gauss View 5.0, Mutiwfn program and website ( https://www.molsoft.com/mprop/mprop.cgi ), respectively.

Molecular simulation of the slurrying mechanism in microplastic semi-coke water slurry.

This study explores the interaction between particles in microplastic semi-coke water slurry at the molecular level using molecular simulation methods, specifically DFT calculations and MD simulations. In addition, the experiment of slurry preparation was carried out to study the viscosity and stability of the slurry. The electrostatic potential analysis shows that the interaction between microplastics and dispersant molecules occurs on atoms with large electronegativity or oxygen-containing functional groups, and the energy gap of frontier molecular orbitals indicated that PVC interacts most easily with the dispersant (0.39eV), followed by PS (1.08eV) and PET (3.65eV). In addition, it is also noted that due to the steric hindrance effect, the adsorption energy was opposite to the DFT calculation results: PET was - 213.338kcal/mol (NNO) which was highest, followed by PS (- 107.603kcal/mol, NNO), and PVC (NNO) was lowest which was - 94.808kcal/mol. And RDF shows similar results, which the probability of water molecules in the PET system was the highest, followed by PS, and finally, PVC. The MD results are consistent with the viscosity and stability characterization results of the slurry which PET has the lowest viscosity of 87.3mPa·s. Finally, this study provides new ideas for the treatment of microplastics and the improvement of the performance of semi-coke water slurry and reveals the interaction mechanism between microplastics and semi-coke water slurry. All calculations were performed using Materials Studio (MS) version 2020 software, BIOVIA Corporation. The DFT calculation was carried out through the DMol3 module. The DFT calculations include electron density, electrostatics, orbitals, and population analysis. In DMol3 module, the GGA-PBE function was selected to consider gradient changes in density in the simulated calculation. The DFT-D correction was selected, and all electrons were calculated by DNP for accurate core potentials and the DNP file was 4.4. MD simulation was performed through the Forcite module. MD simulation mainly focuses on relative concentration distribution analysis, radial distribution function, and adsorption energy calculation. All molecular geometry optimizations are performed in the Forcite module. In the molecular dynamic part, all simulations used PCFF forcefield. The NVT ensemble was adopted and using the Nosé thermostat.

Insights into the electronic structure and interaction energies of 4-ethoxy-N-(4-ethoxy-2-hydoxybenzylidene)benzohydrazide

The molecule 4-ethoxy-N-(4-ethoxy-2-hydroxybenzylidene)benzohydrazide (4EHB) is characterized by a rigid aroylhydrazone core, acting as a mesogenic unit, and a flexible chain at its terminal end. The aroylhydrazone core comprises two aromatic rings linked by connecting groups, resulting in moderate size and elongation of the molecule. Variations in the positions and orientations of elongated molecules give rise to different mesogenic phases such as Nematic, Smectic, and Hexatic Smectic. The mesogenic behavior of aroylhydrazone-based materials is governed by various non-covalent interactions. In this study, molecular geometry optimization, analysis of HOMO-LUMO orbitals, and MEP surfaces of individual and pairs of 4EHB molecules were conducted using the Density functional B3LYP technique with the basis set 6-31G**. Intermolecular interaction energies between pairs of 4EHB molecules are evaluated using the technique M06-2X/6-311G** in stacking, terminal, and side-to-side (in-plane) configurations. Basis set superposition error (BSSE) is corrected using counterpoise method and interaction energy(I.E.) is decomposed in different components using SAPT0 method at level 6-311G**, which provided insights into the mesogenic behavior of the system.

Evaluation of the Xtb Semiempirical Method for the Prediction of Antioxidant Properties in Alzheimer’s Disease: Salen-Type Ligands

Alzheimer’s disease (AD) stands as the predominant form of dementia, accounting for up to 70% of all cases worldwide. AD is a complex disease with various contributing factors. Evidence suggests that the metalliccomplexes formed by the β-amyloid peptide (Aβ) and extraneuronal copper can catalyze the generation ofreactive oxygen species, consequently increasing oxidative stress and contributing to the decline of neurons. This interaction underscores the significance of bioavailable copper as a crucial redox-active target in exploring protocols for multifunctional agents in AD treatment. In the field of computational chemistry, density functional theory (DFT) is widely accepted as a standard method across different disciplines. Despite this, DFT presents computational challenges, particularly in screening extensive molecular sets during the initial phases of drug research. Recent advances in semiempirical quantum mechanical methods (SQM) offer a promising alternative, providing rapid molecular geometry optimization and approximate estimation of thermodynamical properties, being at least two orders of magnitude faster than traditional DFT calculations. In this work, we present an evaluation of the GFNn-xTB SQM methods in the rapid screening of antioxidant properties in AD, performed on a set of salen ligands by calculating the standard reduction potentials of their copper complexes as key property. Results show that the implementation of GFNn-xTB SQM calculations before DFT evaluations is

Synthesis, physicochemical and quantum chemical studies of 7-azaindolinium-3,5-dinitrobenzoate single crystal for nonlinear optical applications

Abstract A novel hydrogen bonded single crystal of 7-azaindolinium-3,5-dinitrobenzoate (7AIDNB) has been grown, and the structure of the crystal was determined by single-crystal XRD analysis. The results show that the grown crystal belongs to a triclinic crystal system with centrosymmetric space group P-1 and the unit cell parameters: a = 6.998(9) Å, b = 8.498(12) Å, c = 13.103(17) Å, V = 710.78(17) Å3, Z = 2. The presence of expected discrete functional groups in 7AIDNB has been identified by an FT-IR spectroscopic study. The thermal stability and decomposition of the title crystal have been studied by TG-DTA analysis. The optical property of the grown crystal has been analyzed by UV-Vis-NIR spectroscopy analysis. The DFT with 6-311++G(d, p) basis set has been used to examine optimization of molecular geometry, Mulliken charge, and HOMO-LUMO. As the frequency of the grown crystal increases, the dielectric loss and dielectric constant decrease. The third-order NLO parameters of 7AIDNB have been examined by a Z-scan technique.

MolOpt: Autonomous Molecular Geometry Optimization Using Multiagent Reinforcement Learning.

Most optimization problems require the user to select an algorithm and, to some extent, also tune it for better performance. Although intuition and knowledge about the problem can speed up these selection and fine-tuning processes, users often use trial-and-error methodologies, which can be time-consuming and inefficient. With all of that in mind and much more, the concept of "learned optimizers", "learning to learn", and "meta-learning" has been gathering attention in recent years. In this article, we propose MolOpt that uses multiagent reinforcement learning (MARL) for autonomous molecular geometry optimization (MGO). Typically MGO algorithms are hand-designed, but MolOpt uses MARL to learn a learned optimizer (policy) that can perform MGO without the need for other hand-designed optimizers. We cast MGO as a MARL problem, where each agent corresponds to a single atom in the molecule. MolOpt performs MGO by minimizing the forces on each atom of the molecule. Our experiments demonstrate the generalizing ability of MolOpt for the MGO of propane, pentane, heptane, hexane, and octane when trained on ethane, butane, and isobutane. In terms of performance, MolOpt outperforms the MDMin optimizer and demonstrates performance similar to that of the FIRE optimizer. However, it does not surpass the BFGS optimizer. The results demonstrate that MolOpt has the potential to introduce innovative advancements in MGO by providing a novel approach using reinforcement learning (RL), which may open up new research directions for MGO. Overall, this work serves as a proof-of-concept for the potential of MARL in MGO.

Integrating Chemical Information into Reinforcement Learning for Enhanced Molecular Geometry Optimization.

Geometry optimization is a crucial step in computational chemistry, and the efficiency of optimization algorithms plays a pivotal role in reducing computational costs. In this study, we introduce a novel reinforcement-learning-based optimizer that surpasses traditional methods in terms of efficiency. What sets our model apart is its ability to incorporate chemical information into the optimization process. By exploring different state representations that integrate gradients, displacements, primitive type labels, and additional chemical information from the SchNet model, our reinforcement learning optimizer achieves exceptional results. It demonstrates an average reduction of about 50% or more in optimization steps compared to the conventional optimization algorithms that we examined when dealing with challenging initial geometries. Moreover, the reinforcement learning optimizer exhibits promising transferability across various levels of theory, emphasizing its versatility and potential for enhancing molecular geometry optimization. This research highlights the significance of leveraging reinforcement learning algorithms to harness chemical knowledge, paving the way for future advancements in computational chemistry.

Talarolide A and Talaropeptides A-D: Potential Marine-Derived Therapeutic Peptides with Interesting Chemistry and Biological Activity Studied through Density Functional Theory (DFT) and Conceptual DFT.

Molecules sourced from marine environments hold immense promise for the development of novel therapeutic drugs, owing to their distinctive chemical compositions and valuable medicinal attributes. Notably, Talarolide A and Talaropeptides A-D have gained recent attention as potential candidates for pharmaceutical applications. This study aims to explore the chemical reactivity of Talarolide A and Talaropeptides A-D through the application of molecular modeling and computational chemistry techniques, specifically employing Conceptual Density Functional Theory (CDFT). By investigating their chemical behaviors, the study seeks to contribute to the understanding of the potential pharmacological uses of these marine-derived compounds. The molecular geometry optimizations and frequency calculations were conducted using the Density Functional Tight Binding (DFTBA) method. This was followed by a subsequent round of geometry optimization, frequency analysis, and computation of electronic properties and chemical reactivity descriptors. We employed the MN12SX/Def2TZVP/H2O model chemistry, utilizing the Gaussian 16 program and the SMD solvation model. The analysis of the global reactivity descriptors arising from CDFT was achieved as well as the graphical comparison of the dual descriptor DD revealing the areas of the molecules with more propensity to suffer a nucleophilic or electrophilic attack. Additionally, Molinspiration and SwissTargetPrediction were considered for the calculation of molecular characteristics and predicted biological targets. These include enzymes, nuclear receptors, kinase inhibitors, GPCR ligands, and ion channel modulators. The graphical results show that Talarolide A and the Talaropeptides A-D are likely to behave as protease inhibitors.

Experimental, spectroscopic, and theoretical investigation on structural and anticancer activities of Schiff bases derived from isonicotinohydrazide

Isoniazid hydrazones are promising possibilities as medicines since they have preserved efficacy and are less toxic and resistant to resistance than parent Isoniazid (INH). Here, we have synthesized a series of Schiff bases (INH1–9) derived from a clinically approved antitubercular drug Isoniazid (INH). These synthesized ligands have been characterized by various spectroscopic techniques like IR, UV–vis., NMR, HRMS, etc. Moreover, single crystal of three derivatives viz. INH4, INH8, and INH9 has been determined and they crystallize in monoclinic crystal system. Hirshfeld surface analysis has been performed to ascertain intermolecular interactions present in these compounds. The molecular geometry optimization and vibrational analysis of these compounds were performed using density functional theory (DFT) studies utilizing B3LYP/6–31++G(d, p) basis set. The TD-DFT analysis was also performed to understand electronic transitions and the nature of FMO in these compounds. There was a good correlation found between theoretical and experimental values, thereby confirming the molecular structures of synthesized compounds. Molecular docking studies were performed to obtain more insights on potential anticancer activities of these compounds along with standard anticancer drugs 5-fluorouracil and Tamoxifen against MDM2 (4HG7) protein. The outcome revealed a significant binding affinity of these compounds with target protein even better than 5-fluorouracil and comparable to Tamoxifen. The compounds (INH4 and INH9) having the strongest binding affinity with the target protein are further experimentally evaluated for their in-vitro cytotoxic action on Dalton's lymphoma cells employing MTT assay, fluorescence microscopy, and flow cytometry. IC50 value (150 µg/ml) of this compound is equated with before-reported complexes/molecules/extracts and found it has better or comparable cytotoxicity.

Vibrational spectroscopic studies, DFT, and molecular docking investigations of 4-fluoro- 3-methyl benzophenone

Potential energy distribution was used to describe the optimum molecular geometry, FT-IR, FT-Raman, and UV-Vis spectra, vibrational frequency bands, and assignment of suitable vibrational modes of 4-fluoro-3-methyl benzophenone. Utilizing DFT/B3LYP with a 6–31 +G level, spectroscopic investigations are conducted. The findings of the computation were utilized to model 4-fluoro-3-methyl benzophenone, which has a very good correlation with the spectra that were observed. The TDFT was used so that oscillator strengths could be determined. In order to determine how much charge was transferred by the molecule, HOMO and LUMO analyses were performed. Through the use of the NBO analysis, it was feasible to determine the existence of internal charge transfer, hyperconjugation, and stabilizing energy. DFT techniques were applied to investigate Mulliken's charges and hyperpolarizability characteristics. In the molecular docking investigation, the 4-Fluoro-3-methylbenzophenone molecule was docked with Prostaglandin H2 Synthase-1 and Prostaglandin H2 Synthase-2. Due to their hormone-like properties, the phospholipid molecules known as prostaglandins (PGs) play a crucial part in the body's pain and inflammatory responses. These compounds are composed of fatty acids, which are prevalent in cell membranes. Membrane-associated enzyme cyclooxygenase (COX) is responsible for this process. There are two isoforms of this enzyme: COX-1 and COX-2.

Synthesis, structural characterization and antibacterial activity evaluation of novel quinolone-1,2,3-triazole-benzimidazole hybrids

In this investigation, a series of 2-quinolone-benzimidazole hybrids linked by a 1,2,3-triazole moiety were prepared using copper-catalyzed Huisgen 1,3-dipolar cycloaddition and condensation reaction. The newly synthesized compounds were characterized by 1H NMR, 13C NMR, single crystal XRD and HRMS analysis. The density functional theory (DFT) calculations were performed using B3LYP/6–31+G (d,p) basis level set for the optimization of molecular geometries of compounds 7a, 7c, 7f and 7l The conformational analysis predicted the existence of two main conformations: a closed and an open conformation. In vitro antibacterial activity was assessed against Gram-positive bacterium Staphylococcus aureus (S. aureus) and Gram-negative bacterium Escherichia coli (E. coli). The bioassays revealed that compounds 7a, 7c, 7f and 7l inhibited the growth of E. coli at a concentration of 0.14 µmol/mL, which was nearly 2-fold stronger than the control drug ampicillin (0.26 µmol/mL). Besides, compounds 7f and 7l exhibited the most promising activity against S. aureus with MIC and MBC values of 0.07 µmol/mL for 7f and 0.14 µmol/mL for 7l compared to 0.27 µmol/mL for ampicillin. These results were supported by the chemical reactivity parameters and electrostatic surface potential (MEP) obtained using theoretical calculations. Molecular docking study of the most active compounds using DNA gyrase A and DNA gyrase B proteins of S. aureus also confirmed the experimental findings.

A spur to molecular geometry optimization: Gradient-enhanced universal kriging with on-the-fly adaptive ab initio prior mean functions in curvilinear coordinates.

We present a molecular geometry optimization algorithm based on the gradient-enhanced universal kriging (GEUK) formalism with ab initio prior mean functions, which incorporates prior physical knowledge to surrogate-based optimization. In this formalism, we have demonstrated the advantage of allowing the prior mean functions to be adaptive during geometry optimization over a pre-fixed choice of prior functions. Our implementation is general and flexible in two senses. First, the optimizations on the surrogate surface can be in both Cartesian coordinates and curvilinear coordinates. We explore four representative curvilinear coordinates in this work, including the redundant Coulombic coordinates, the redundant internal coordinates, the non-redundant delocalized internal coordinates, and the non-redundant hybrid delocalized internal Z-matrix coordinates. We show that our GEUK optimizer accelerates geometry optimization as compared to conventional non-surrogate-based optimizers in internal coordinates. We further showcase the power of the GEUK with on-the-fly adaptive priors for efficient optimizations of challenging molecules (Criegee intermediates) with a high-accuracy electronic structure method (the coupled-cluster method). Second, we present the usage of internal coordinates under the complete curvilinear scheme. A complete curvilinear scheme performs both surrogate potential-energy surface (PES) fitting and structure optimization entirely in the curvilinear coordinates. Our benchmark indicates that the complete curvilinear scheme significantly reduces the cost of structure minimization on the surrogate compared to the incomplete curvilinear scheme, which fits the surrogate PES in curvilinear coordinates partially and optimizes a structure in Cartesian coordinates through curvilinear coordinates via the chain rule.

Machine Learning Diffusion Monte Carlo Forces

Diffusion Monte Carlo (DMC) is one of the most accurate techniques available for calculating the electronic properties of molecules and materials, yet it often remains a challenge to economically compute forces using this technique. As a result, ab initio molecular dynamics simulations and geometry optimizations that employ Diffusion Monte Carlo forces are often out of reach. One potential approach for accelerating the computation of "DMC forces" is to machine learn these forces from DMC energy calculations. In this work, we employ Behler-Parrinello Neural Networks to learn DMC forces from DMC energy calculations for geometry optimization and molecular dynamics simulations of small molecules. We illustrate the unique challenges that stem from learning forces without explicit force data and from noisy energy data by making rigorous comparisons of potential energy surface, dynamics, and optimization predictions among ab initio density functional theory (DFT) simulations and machine-learning models trained on DFT energies with forces, DFT energies without forces, and DMC energies without forces. We show for three small molecules─C2, H2O, and CH3Cl─that machine-learned DMC dynamics can reproduce average bond lengths and angles within a few percent of known experimental results at one hundredth of the typical cost. Our work describes a much-needed means of performing dynamics simulations on high-accuracy, DMC PESs and for generating DMC-quality molecular geometries given current algorithmic constraints.

Duplex DNA Retains the Conformational Features of Single Strands: Perspectives from MD Simulations and Quantum Chemical Computations.

Molecular dynamics simulations and geometry optimizations carried out at the quantum level as well as by quantum mechanical/molecular mechanics methods predict that short, single-stranded DNA oligonucleotides adopt conformations very similar to those observed in crystallographic double-stranded B-DNA, with rise coordinates close to ≈3.3 Å. In agreement with the experimental evidence, the computational results show that DNA single strands rich in adjacent purine nucleobases assume more regular arrangements than poly-thymine. The preliminary results suggest that single-stranded poly-cytosine DNA should also retain a substantial helical order in solution. A comparison of the structures of single and double helices confirms that the B-DNA motif is a favorable arrangement also for single strands. Indeed, the optimal geometry of the complementary single helices is changed to a very small extent in the formation of the duplex.

Insights into solvent effects on molecular properties, physicochemical parameters, and NLO behavior of brinzolamide, a bioactive sulfonamide: A computational study

In this study, quantum chemical calculations performed on brinzolamide (BZ), a sulfonamide derivative widely used as an antibacterial and antifungal drug, are presented. The molecular geometry optimizations of BZ were calculated by using both B3LYP functional and HF method with the 6-31G (d, p) basis set via Gaussian software. Since solvent phase behaviors are extremely important especially for drug molecules, calculations were renewed for BZ in ten different solvent environments. Universal solvation model SMD (Solvent Model based on Density) was utilized for solvent phase simulations. Mulliken and natural atomic charges, frontier molecular orbital (FMO) energies, quantum chemical descriptors were studied in detail according to solvent and method variation. In addition, the partition coefficient (logPow) value, which is an important parameter for the activity of the drug candidates, was theoretically estimated according to the relevant formula through the computed values for the water and 1-octanol phases for each methodology. The slightly lipophilic character of the BZ molecule was supported by the obtained values and the molecular lipophilicity potential map prepared by means of Molinspiration Galaxy 3D Structure Generator v2018.01 beta program. In the nonlinear optical (NLO) property analysis, dipole moment (μtot), mean polarizability (αtot), anisotropic polarizability (Δα), and mean first-order hyperpolarizability (βtot) values of BZ and the solvent effect on these values have been reported. Last, the interaction energies between donor and acceptor orbitals were calculated by the analysis of natural bond orbitals, and the obtained results were summarized.

Theoretical study of the Meisenheimer and charge-transfer complexes formed upon colorimetric determination of nitroaromatic explosives

In this paper, we present a theoretical study of structure and UV-vis spectra of 11 colored complexes of nucleophiles with nitroaromatic energetic materials. Two different schemes were found to be the most suitable for absorption spectra simulation. In the case of covalently bound Meisenheimer complexes, the time-dependent density functional theory (TD-DFT) approach with the TPSS functional was the most accurate. Meanwhile, for intermolecular charge-transfer complexes, the closest spectral pattern was provided by the time-dependent Hartree-Fock (TD-HF) scheme with modified exchange contribution (40%). It has been found that the binding type is determined predominantly by the steric factors and less by the electronic effects of the nucleophile, which was approved by the quantum theory of atoms in molecules (QTAIM) analysis of the formed bond types and nucleophilicity index calculations. For the charge-transfer complex, an appropriate configuration with the intermolecular separation between the local electrophilic and nucleophilic sites (the C1···N distance) of about 3.1 Å, was revealed using both classical molecular dynamics simulations and geometry optimizations in polar continuum. Absorption energies and intensities of the electronic transitions are generally well-reproduced in all 11 cases and demonstrate a local π–π* excitation in the covalently-bound complexes and pure charge transfer in intermolecular system. The applied computational methods allow reproducing of the sample colors with a high degree of similarity, which may find their application for modeling of new reagents with other expected colorimetric characteristics.