Solvation Model Research Articles

Potential and electric double-layer effect in electrocatalytic urea synthesis

Electrochemical synthesis is a promising way for sustainable urea production, yet the exact mechanism has not been fully revealed. Herein, we explore the mechanism of electrochemical coupling of nitrite and carbon dioxide on Cu surfaces towards urea synthesis on the basis of a constant-potential method combined with an implicit solvent model. The working electrode potential, which has normally overlooked, is found influential on both the reaction mechanism and activity. The further computational study on the reaction pathways reveals that *CO-NH and *NH-CO-NH as the key intermediates. In addition, through the analysis of turnover frequencies under various potentials, pressures, and temperatures within a microkinetic model, we demonstrate that the activity increases with temperature, and the Cu(100) shows the highest efficiency towards urea synthesis among all three Cu surfaces. The electric double-layer capacitance also plays a key role in urea synthesis. Based on these findings, we propose two essential strategies to promote the efficiency of urea synthesis on Cu electrodes: increasing Cu(100) surface ratio and elevating the reaction temperature.

Hybrid Improved Grey Wolf Support Vector Regression Algorithm for Modeling Solubilities of APIs in Pure Ionic Liquids: σ-Profile Descriptors.

The objective of this study was to model the solubility of active pharmaceutical ingredients (APIs) in different ionic liquids (ILs) based on the σ-moments of cations, anions, and APIs that were used as molecular descriptors calculated using the σ-profiles of three categories of descriptors based on conductor-like screening model for real solvents. The database of 83 API-ILs systems composed of 14 APIs, 12 cations, and 7 anions (25 ILs combinations) was collected as 850 data points at different temperature ranges. A hybrid Improved Grey Wolf Support vector regression, abbreviated as I-GWO-SVR(r), algorithm was selected as the learning method. Based on a comprehensive comparison with 11 different models, various statistical factors, and graphical analyses, including an external validation test, analysis of variance (ANOVA), and sensitivity analysis, the capability and validity of the proposed approach have been assessed and verified. The overall study confirmed that the proposed new model provided the best results in terms of predicting the solubility of APIs in ILs.

Limiting factors in the accuracy of DFT calculation for redox potentials.

In the present study, we have investigated factors affecting the accuracy of computational chemistry calculation of redox potentials, namely the gas-phase ionization energy (IE) and electron affinity (EA), and the continuum solvation effect. In general, double-hybrid density functional theory methods yield IEs and EAs that are on average within ~0.1 eV of our high-level W3X-L benchmark, with the best performing method being DSD-BLYP/ma-def2-QZVPP. For lower-cost methods, the average errors are ~0.2-0.3 eV, with ωB97X-3c being the most accurate (~0.15 eV). For the solvation component, essentially all methods have an average error of ~0.3 eV, which shows the limitation of the continuum solvation model. Curiously, the directly calculated redox potentials show errors of ~0.3 eV for all methods. These errors are notably smaller than what can be expected from error propagation with the two components (IE and EA, and solvation effect). Such a discrepancy can be attributed to the cancellation of errors, with the lowest-cost GFN2-xTB method benefiting the most, and the most accurate ωB97X-3c method benefiting the least. For organometallic species, the redox potentials show large deviations exceeding ~0.5 eV even for DSD-BLYP. The large errors are attributed to those for the gas-phase IEs and EAs, which represents a major barrier to the accurate calculation of redox potentials for such systems.

Predicting sulfanilamide solubility in the binary mixtures using a reference solvent approach.

Solubility is a fundamental physicochemical property of active pharmaceutical ingredients. The optimization of a dissolution medium aims not only to increase solubility and other aspects are to be included such as environmental impact, toxicity degree, availability, and costs. Obtaining comprehensive solubility characteristics of chemical compounds is a non-trivial and demanding process. Therefore, support from theoretical approaches is of practical importance. This study aims to examine the accuracy of the reference solubility approach in the case of sulfanilamide dissolution in a variety of binary solvents. This pharmaceutically active substance has been extensively studied, and a substantial amount of solubility data is available. Unfortunately, using this set of data directly for theoretical modeling is impeded by noticeable inconsistencies in the published solubility data. Hence, this aspect is addressed by data curation using theoretical and experimental confirmations. In the experimental part of our study, the popular shake-flask method combined with ultraviolet (UV) spectrophotometric measurements was applied for solubility determination. The computational phase utilized the conductor-like screening model for real solvents (COSMO-RS) approach. The analysis of the results of solubility calculations for sulfonamide in binary solvents revealed abnormally high error values for acetone-ethyl acetate mixtures, which were further confirmed with experimental measurements. Additional confirmation was obtained by extending the solubility measurements to a series of homologous acetate esters. Our study addresses the crucial issue of coherence of solubility data used for many theoretical inquiries, including parameter fitting of semi-empirical models, in-depth thermodynamic interpretations and application of machine learning protocols. The effectiveness of the proposed methodology for dataset curation was demonstrated for sulfanilamide solubility in binary mixtures. This approach enabled not only the formulation of a consistent dataset of sulfanilamide solubility binary solvent mixtures, but also its implementation as a qualitative tool guiding rationale solvent selection for experimental solubility screening.

Modeling the aqueous ionic environment of biomolecules with the 3D-reference interaction site model of molecular solvation

Modeling the aqueous ionic environment of biomolecules with the 3D-reference interaction site model of molecular solvation

Computational study on organochlorine insecticides extraction using ionic liquids

Insecticides pose hazardous environmental effects and can enter the food chain and contaminate water resources. Ionic liquids (ILs) have recently drawn much interest as environmentally friendly solvents and have been an efficient choice for extracting pesticides because of their outstanding thermophysical characteristics and tunable nature. In this study, ILs were screened using COSMO-RS (Conductor-like Screening Model for Real Solvents) to extract organochlorine insecticides from water at 289 K. A total of 165 ILs, a combination of 33 cations with five anions, were screened by COSMO-RS to predict the selectivity and capacity of the organochlorine insecticides at infinite dilution. The Organochlorine insecticide compounds, such as benzene hexachloride (BHC), Heptachlor, Aldrin, Gamma-Chlordane (γ-Chlordane), Endrin, and Methoxychlor are selected for this study. Charge density profiles show that Endrin and Methoxychlor compounds are strong H-bond acceptors and weak H-bond donors, while the rest of the compounds are H-bond donors with no H-bond acceptor potential. Moreover, it has been shown that ILs composed of halides and heteroatomic anions in conjunction with cations have enhanced selectivity and capacity for insecticides. Moreover, the hydrophobic phosphonium-based ILs have enhanced selectivity and capacity for insecticides. In BHC extraction, the selectivity of 1,3-dimethyl-imidazolium chloride was found to be the highest at 1074.06, whereas 2-hydroxyethyl trimethyl ammonium chloride exhibited the highest capacity being 84.0.1,3-dimethyl-imidazolium chloride exhibits the highest performance index, which is 57064.77. In addition, the ILs that have been chosen are well-recognized as environmentally friendly and very effective solvents to extract insecticides from water. As a result, this study evaluated that ILs could be promising solvents that may be further developed for the extraction of insecticides from contaminated water.

Effective removal of personal care product residues from aqueous media using hydrophobic deep eutectic solvents: Experimental and computational approach

Personal care product (PCP) residues - classified under micropollutants (MPs)- are widely found in aquatic environments, posing trace-level toxicity. Traditional water treatment techniques struggle to remove these toxins effectively. Deep eutectic solvents (DESs), the liquid mixtures typically composed of hydrogen bond donors (HBDs) and hydrogen bond acceptors (HBAs), have recently emerged as a viable alternative for extracting pollutants from water. Among DESs, hydrophobic deep eutectic solvents (HDESs) exhibit low water miscibility and unique solvent properties. The main objective of this study is to synthesize HDESs to effectively eliminate 2-naphthol and methylparaben- two of the significant chemical contaminants in PCPs- from aqueous media. HDESs were prepared by mixing different terpenes (menthol and thymol) and long-chain carboxylic acids at varying molar ratios. They were characterized using different spectroscopic and thermal techniques. The density and viscosity of the pure DESs were measured as afunction of temperature. Experimental studies were carried out using the liquid–liquid extraction (LLE) method, and the factors influencing the efficiency of extraction were optimized.Considering the limited number of studies on the extraction mechanism of MPs from aqueous media, this study employs comprehensive computational methods, including density functional theory (DFT) and the COnductor-like Screening MOdel for Real Solvents (COSMO-RS), to provide a detailed interpretation of the extraction mechanism. A series of successive extractions were conducted to reduce the DES usage to ensure economic viability. The reusability of the best-performed DES was explored. Additionally, the regeneration of one of the DESs was accomplished through activated carbon-based recovery.---------------------------------------------------------------------------------------------------------------------

Precise Engineering of the Electrocatalytic Activity of FeN4-Embedded Graphene on Oxygen Electrode Reactions by Attaching Electrides.

Using first-principles calculations combined with a constant-potential implicit solvent model, we comprehensively studied the activity of oxygen electrode reactions catalyzed by electride-supported FeN4-embedded graphene (FeN4Cx). The physical quantities in FeN4Cx/electrides, i.e., work function of electrides, interlayer spacing, stability of heterostructures, charge transferred to Fe, d-band center of Fe, and adsorption free energy of O, are highly intercorrelated, resulting in activity being fully expressed by the nature of the electrides themselves, thereby achieving a precise modulation in activity by selecting different electrides. Strikingly, the FeN4PDCx/Ca2N and FeN4PDCx/Y2C systems maintain a high oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) activity with the overpotential less than 0.46 and 0.62 V in a wide pH range. This work provides an effective strategy for the rational design of efficient bifunctional catalysts as well as a model system with a simple activity-descriptor, helping to realize significant advances in energy devices.

Development of a multi-step screening procedure for redox active molecules in organic radical polymer anodes and as redox flow anolytes.

Benzo[d]-X-zolyl-pyridinyl (XO, S, NH) radicals represent a promising class of redox-active molecules for organic batteries. We present a multistep screening procedure to identify the most promising radical candidates. Experimental investigations and highly correlated wave function-based calculations are performed to determine benchmark redox potentials. Based on these, the accuracies of different methods (semi-empirical, density functional theory, wave function-based), solvent models, dispersion corrections, and basis sets are evaluated. The developed screening procedure consists of three steps: First, a conformer search is performed with CREST. The molecules are selected based on the redox potentials calculated using GFN2-xTB. Second, HOMO energies calculated with reparametrized B3LYP-D3(BJ) and the def2-SVP basis set are used as selection criteria. The final molecules are selected based on the redox potentials calculated from Gibbs energies using BP86-D3(BJ)/def2-TZVP. With this multistep screening approach, promising molecules can be suggested for synthesis, and structure-property relationships can be derived.

Evaluation of Thermodynamic and Kinetic Contributions to Over-Extraction of Extractables by Nonpolar Organic Solvents in Comparison to Lipids in Exhaustive and Exaggerated Extractions of Medical Devices Based on Abraham Solvation Model and Solvent–Material Interactions Using Low-Density Polyethylene as a Representative Material

The thermodynamic and kinetic contributions to the over-extraction of extractables by nonpolar organic solvents relative to biological lipids in exhaustive and exaggerated extractions of medical devices are studied based on the Abraham solvation model and solvent–material interactions, using low-density polyethylene (LDPE) as an exemplary material. The thermodynamic effect is evaluated by the partition constant of extractables between LDPE and extraction solvents, hexane and lipids, defined as the concentration in the polymer phase divided by the concentration in the solvent phase. The Abraham solvation model is used to correlate the measured LDPE-lipid partition constant (log10Pldpe/lipid) to construct the predictive model. Similar models are also derived from the thermodynamic cycle conversion, using the system constants of LDPE-water and Lipid-water partition systems. These constructed models, together with the predictive LDPE-hexane (log10Pldpe/hexane) model established from a previous study, are used to predict and compare the ranges and values of Pldpe/s (s = lipids and hexane) for the observed LDPE extractables over a wide hydrophobicity range in log10Po/w from zero to 30. The solvent-LDPE interactions are examined by the degree of swelling of LDPE by hexane (or other nonpolar solvents) and lipids, including the solvent diffusion rates into the material. These parameters allow the evaluation of kinetic effect on the over-extraction. The extent of over-extraction is compiled directly by experimental “overall” or “specific” migration data or indirectly calculated by the diffusion coefficient of extractables when extracted by hexane or lipids. It is concluded from this study that the extractables distribution between LDPE and lipids highly favors the lipid phase thermodynamically (Pldpe/lipid<1), and the values of Pldpe/lipid are always lower than those of Pldpe/hexane, thereby indicating that the thermodynamic effect is not the cause of over-extraction. It is the kinetic effect that dominantly contributes to the over-extraction, as supported by the material swelling and solvent diffusion rates. Finally, the extent of over-extraction has been established from a few folds to over a hundred-fold, and the median value is 7. Furthermore, the methods adopted and developed in this study can be invaluable tools in other disciplines such as the reliable prediction of extractables from other device materials and environmental sampling.

The enhanced electro/photocatalytic activity for nitric oxide reduction to ammonia by B@g-C9N10 monolayer

Selective electro/photocatalytic reduction of nitride oxide (NO) to ammonia (NH3) provides a promising way to remove the pollutant under ambient conditions. The key to NO reduction reaction (NORR) is to develop more economical and efficient electrocatalysts compared to the industrialized Pt-based catalysts. In this work, the boron atom doping g-C9N10 monolayer (B@g-C9N10) is designed and the electro/photocatalytic NORR performance is systematically investigated by means of density functional theory (DFT). Among the N-end, O-end and side-on structures, the N-end NO adsorption is found to be the most stable one, which greatly favors the NO activation by the “σ-donation and π* back-donation” mechanism. Among the N-distal, N-alternating, O-distal, O-alternating, Mixed 1–3 hydrogenation pathways in the electrocatalytic process, the O-alternating and Mixed-2 pathways are the most efficient NORR routes, which have the same limiting potential (UL) of −0.386 V in the step of *NH2→*NH3. However, the NO molecule is more easily activated in *N–OH along O-alternating pathway than Mixed-2 pathway. The energy barrier can be further decreased by considering the implicit and explicit solvation model and the NH3 selectivity of B@g-C9N10 is higher than N2O, N2 and H2. The irradiating energy of 1.094 eV can decrease the reaction energy, resulting in the spontaneous NORR process along Mixed-2 pathway. Our findings uncover a promising approach to design a bifunctional NORR electro/photocatalyst with high NH3 selectivity and activity NO→NH3 conversion.

Sustainable In Silico-Supported Ultrasonic-Assisted Extraction of Oligomeric Stilbenoids from Grapevine Roots Using Natural Deep Eutectic Solvents (NADES) and Stability Study of Potential Ready-to-Use Extracts.

Grapevine roots, as a side-stream of a vineyard, are a sustainable resource for the recovery of oligomeric stilbenoids, such as the bioactive r-viniferin. The aim of this study is to evaluate an in silico-supported method, based on the Conductor-like Screening Model for Real Solvents (COSMO-RS), for selection of environmentally friendly natural deep eutectic solvents (NADES) with regard to the extraction of grapevine roots. The most suitable NADES system for ultrasonic-assisted extraction of r-viniferin was choline chloride/1,2-propanediol. The optimal extraction parameters for r-viniferin were determined using single-factor experiments as follows: choline chloride/1,2-propanediol 1/2 mol/mol, 10 wt% H2O, biomass/NADES ratio 1/10 g/g, and 10 min extraction time. Under optimized conditions, the extraction yield of r-viniferin from grapevine roots reached 76% of the total r-viniferin content. Regarding stability, stilbenoids in choline chloride/1,2-propanediol remained stable during 128 days of storage at ambient temperature. However, fructose/lactic acid-based NADES were observed to degrade stilbenoids; therefore, the removal of the NADES will be of interest, with a suitable method implemented using Amberlite® XAD-16N resin. As green solvents, the NADES have been used as effective and environmentally friendly extractants of stilbenoid-containing extracts from grapevine roots for potential applications in the cosmetic and pharmaceutical industry or as nutraceuticals in the food industry.

Unraveling the mystery of solvation-dependent fluorescence of fluorescein dianion using computational study.

Fluorescein, one of the brightest fluorescent dye molecules, is a widely used fluorophore for various applications from biomedicine to industry. The dianionic form of fluorescein is responsible for its high fluorescence quantum yield. Interestingly, the molecule was found to be nonfluorescent in the gas phase. This characteristic is attributed to the photodetachment process, which out-competes the fluorescence emission in the gas phase. In this work, we show that the calculated vertical and adiabatic detachment energies of fluorescein dianion in the gas and solvent phases account for the drastic differences observed in their fluorescence characteristics. The functional dependence of these detachment energies on the dianion's microsolvation was systematically investigated. The performance of different solvent models was also assessed. The higher thermodynamic stability of fluorescein dianion over the monoanion doublet in the solvent phase plays a crucial role in quenching photodetachment and activating the radiative channel with a high fluorescence quantum yield.

Comprehensive Investigation of Cu2+ Adsorption from Wastewater Using Olive-Waste-Derived Adsorbents: Experimental and Molecular Insights.

This study investigates the efficacy of adsorbents from locally sourced olive waste-encompassing olive skins, leaves, and pits, recovered from the initial centrifugation of olives (OWP)-and a composite with sodium alginate (OWPSA) for the removal of Cu2+ ions from synthetic wastewater. Experimental analyses conducted at room temperature, with an initial Cu2+ concentration of 50 mg/L and a solid/liquid ratio of 1 g/L, showed that the removal efficiencies were approximately 79.54% and 94.54% for OWP and OWPSA, respectively, highlighting the positive impact of alginate on adsorption capacity. Utilizing statistical physics isotherm models, particularly the single-layer model coupled to real gas (SLMRG), allowed us to robustly fit the experimental data, providing insights into the adsorption mechanisms. Thermodynamic parameters affirmed the spontaneity and endothermic nature of the processes. Adsorption kinetics were interpreted effectively using the pseudo-second-order (PSO) model. Molecular modeling investigations, including the conductor-like screening model for real solvents (COSMO-RS), density functional theory (DFT), and atom-in-molecule (AIM) analysis, unveiled intricate molecular interactions among the adsorbent components-cellulose, hemicellulose, lignin, and alginate-and the pollutant Cu2+, confirming their physically interactive nature. These findings emphasize the synergistic application of experimental and theoretical approaches, providing a comprehensive understanding of copper adsorption dynamics at the molecular level. This methodology holds promise for unraveling intricate processes across various adsorbent materials in wastewater treatment applications.

Hydration of p-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p-$$\\end{document}aminobenzoic acid: structures and non-covalent bondings of aminobenzoic acid-water clusters

ContextMicro-hydration of the aminobenzoic acid is essential to understand its interaction with surrounding water molecules. Understanding the micro-hydration of the aminobenzoic acid is also essential to study its remediation from wastewater. Therefore, we explored the potential energy surfaces (PESs) of the para-aminobenzoic acid-water clusters, ABWn\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_n$$\\end{document}, n=1-10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$n=1-10$$\\end{document}, to study the microsolvation of the aminobenzoic acid in water. In addition, we performed a quantum theory of atoms in molecules (QTAIM) analysis to identify the nature of non-covalent bondings in the aminobenzoic acid-water clusters. Furthermore, temperature effects on the stability of the located isomers have been examined. The located structures have been used to calculate the hydration free energy and the hydration enthalpy of the aminobenzoic acid using the cluster continuum solvation model. The hydration free energy and the hydration enthalpy of the aminobenzoic acid at room temperature are evaluated to be −7.0 kcal/mol and −18.1 kcal/mol, respectively. The hydration enthalpy is in perfect agreement with a previous experimental estimate. Besides, temperature effects on the calculated hydration enthalpy and free energy are reported. Finally, we calculated the gas phase binding energies of the most stable structures of the ABWn\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_n$$\\end{document} clusters using twelve functionals of density functional theory (DFT), including empirical dispersion. The DFT functionals are benchmarked against the DLPNO-CCSD(T)/CBS. We have found that the three most suitable DFT functionals are classified in the following order: PW6B95D3 > MN15 > ω\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\omega $$\\end{document}B97XD. Therefore, the PW6B95D3 functional is recommended for further study of the aminobenzoic acid-water clusters and similar systems.MethodsThe exploration started with classical molecular dynamics simulations followed by complete optimization at the PW6B95D3/def2-TZVP level of theory. Optimizations are performed using Gaussian 16 suite of codes. QTAIM analysis is performed using the AIMAll program.

Inquiring 199Hg NMR Parameters by Combining Ab Initio Molecular Dynamics and Relativistic NMR Calculations.

Ab initio molecular dynamics (AIMD) sampling followed by relativistic density functional theory (DFT) 199Hg NMR calculations were performed for Hg organometallic complexes in water, dimethyl sulfoxide, and chloroform. The spin-orbit coupling, a relativistic effect, is a key factor for predicting δ(Hg) and 1J(Hg-C) accurately, in conjunction with a dynamic treatment of the systems. Good agreement between the theoretical and experimental results is reached by adopting implicit (based on a continuum model) and explicit (solvent molecules treated quantum mechanically) solvation models. Broader trends appearing in the experimental data available in the literature are reproduced by the calculations, and therefore, quantum chemistry is able to assist in the assignment and interpretation of 199Hg NMR data. Less pronounced trends, such as changes in the 199Hg chemical shift in different systems with the same atom types bound to Hg, are too weak to be predicted reliably by the current state-of-the-art theoretical methods based on AIMD sampling and relativistic DFT with hybrid functionals for NMR calculations.

Single rhodium atom embedded two dimensional MoSi2N4: A promising electrocatalyst for oxygen reduction reaction

It is essential to develop electrocatalysts that exhibit excellent performance in the oxygen reduction reaction (ORR) for electrochemical energy applications. Recently, MoSi2N4 monolayer has been synthesized and attracted widespread interest. Herein, we constructed a series of structures by embedding transition metal (TM = Fe, Co, Ni, Cu, Ru, Rh, Pd, Ir, Pt and Au) atom into MoSi2N4 with N vacancy (VN-MSN), denoted as TM@VN-MSN, and investigated their ORR activity systematically by first-principles calculations. It is found that TM@VN-MSN systems are stable and there is charge transfer between TM atom and MoSi2N4. After screening, Rh@VN-MSN has the best ORR catalytic activity with an overpotential of 0.35 V, even lower than that of classical Pt (111). Furthermore, an implicit solvation model is used to evaluate the solvent effect. The volcano plots and scaling relations are established based on free energies of intermediates, and verified ΔG*OH can use as a descriptor to explore the ORR activity on TM@VN-MSN. Moreover, d-band center theory and crystal orbital Hamilton populations (COHP) are used to reveal the ORR activity origin. This work not only provide a promising method for designing a new type of MoSi2N4-based ORR catalysts, but also expands its application in the field of electrocatalysis.

Solvent effects on the structural, spectroscopic, electronic properties, NCI-RDG analysis, molecular docking and molecular dynamics studies of 1-benzyl-indole-3-carbinol

This investigation focuses on the 1-benzyl-indole-3-carbinol (1-benzyl-I3C) molecule and its capacity as a drug to combat breast cancer. The research employs different computational approaches including DFT simulations, molecular docking, and molecular dynamics calculations. The molecular configuration of 1-benzyl-I3C was optimized in the COSMO solvation model, using B3LYP/cc-pVTZ basis set. The modes of vibration of the compound were identified through Potential Energy Distribution (PED) simulations, and the results were found to be consistent with the available FT-IR and Raman data. The analysis of Natural Bond Orbitals (NBO) supports the idea that 1-benzyl-I3C has bioactive properties. The impact of solvents on the electronic characteristics of studied molecule is discussed. The reactive sites of 1-benzyl-I3C were confirmed by the local reactivity descriptors and the molecular electrostatic potential (MEP) surface analyses. Additionally, Non-covalent interaction (NCI) analysis confirms the existence of the Van der Waals interactions in the compound under investigation. Anti-breast cancer activities of the 1-benzyl-I3C molecule were examined based on molecular docking analysis, which reveals a good inhibitor nature of the studied molecule against the progesterone receptor (PR). The molecular dynamics analysis through the RMSD, RMSF, and Rg plots confirms the overall stability of the obtained 1-benzyl-I3C-PR complex.

Implicit and Explicit Solvent Effects on the Global Reactivity and the Density Topological Parameters of the Preferred Conformers of Caespitate

In the search to cover the urgent need to combat infectious diseases, natural products have gained attention in recent years. The caespitate molecule, isolated from the plant Helichrysum caespititium of the Asteraceae family, is used in traditional African medicine. Caespitate is an acylphloroglucinol with biological activity. Acylphloroglucinols have attracted attention for treating tuberculosis due to their structural characteristics, highlighting the stabilizing effect of their intramolecular hydrogen bonds (IHBs). In this work, a conformational search for the caespitate was performed using the MM method. Posteriorly, DFT calculations with the APFD functional were used for full optimization and vibrational frequencies, obtaining stable structures. A population analysis was performed to predict the distribution of the most probable conformers. The calculations were performed in the gas phase and solution using the implicit SMD model for water, chloroform, acetonitrile, and DMSO solvents. Additionally, the multiscale ONIOM QM1/QM2 model was used to simulate the explicit solvent. The implicit and explicit solvent effects were evaluated on the global reactivity indexes using the conceptual-DFT approach. In addition, the QTAIM approach was applied to analyze the properties of the IHBs of the most energetically and populated conformers. The obtained results indicated that the most stable and populated conformer is in the gas phase, and chloroform has an extended conformation. However, water, acetonitrile, and DMSO have a hairpin shape. The optimized structures are well preserved in explicit solvent and the interaction energies for the IHBs were lower in explicit than implicit solvents due to non-covalent interactions formed between the solvent molecules. Finally, both methodologies, with implicit and explicit solvents, were validated with 1H and 13C NMR experimental data. In both cases, the results agreed with the experimental data reported in the CDCl3 solvent.

Impacts of basis sets, solvent models, and NMR methods on the accuracy of 1H and 13C chemical shift calculations for biaryls: a DFT study

Introduction: Biaryls are core structures composed of chiral ligands, organocatalysts, biologically active natural products and biopolymer lignins. In this study, the effects of basis sets, solvent models, and NMR methods on the accuracy of 1H/13C NMR chemical shift calculations for biaryl structures were evaluated. Methods: All calculations were performed using Gaussian09. The GIAO NMR results were observed and extracted using GaussView05. To reduce the systematic error of the calculations, linear regression analysis of the calculated chemical shifts versus the experimental shifts was performed. Results: The tested basis sets showed good 1H/13C results, with CMAE values as low as 0.0425 ppm and 1.09 ppm for 1H and 13C, respectively. The use of solvent models significantly increased the accuracy of the 1H chemical shift calculations. The GIAO method produced more accurate results than did the IGAIM and CSGT methods. Conclusion: This study recommends 6-31G(d,p) and DGDZVP basis sets, IEMPCM and CPCM solvent models, and GIAO NMR methods for the accurate prediction of 1H and 13C chemical shifts for biaryls, assisting in their full structural assignments.