Application of the Multi-standard Methodology for Calculating 1H NMR Chemical Shifts

Borospherene in the Nanohoop: Complexation and Aromaticity of Neutral and Dioxidized Cycloparaphenylene Supramolecules with B40 and C60 Fullerenes

Supramolecular complexes of carbon nanohoops with fullerenes play a key role for the design of novel nanomaterials with technological applications. Herein we investigate with density functional theory (DFT) methods the capability of neutral and dioxidized cycloparaphenylenes (CPPs) to encapsulate all-boron fullerene B40. Our results show that [9]CPP and [10]CPP are feasible host candidates to encapsulate B40 displaying comparable complexation energies with the all-carbon analog [10]CPP⊃C60. Upon dioxidation the host-guest interactions are not affected, whereas the positive charge is delocalized on the CPPs leading to global aromatic character of the hosts. Consequently, the dicationic complexes [n]CPP2+⊃B40 and [10]CPP2+⊃C60 display augmented global shielding cones that strongly shield the guests, as manifested by large upfield shifts in 11B-NMR and 13C-NMR signals. Hence, CPP complexes with carbon fullerenes can be extended borospherene B40 host-guest complexes, as well as to doubly oxidized species stabilized by global host aromaticity, expanding our understanding of carbon nanohoop complexes to boron-based fullerenes.

An Integrated ANN-PRA/DP4+ Tandem Computational Approach Contributing to the Ordering of the Heliannuol Family

Heliannuols are a unique class of sesquiterpenes isolated mostly from Helianthus annuus, commonly known as sunflower. The interesting allelopathic properties, combined with their unprecedented carbon skeletons, have drawn wide attention to phytochemistry and synthetic groups. So far, 14 heliannuols (heliannuols A-N) have been described in the literature, although some of them have not yet been validated by total synthesis. Moreover, the structural proposal of some compounds was based on the similarity of NMR data reported for previously isolated analogues (which in many instances turned out to be incorrect), coupled with little or no stereochemical analysis. Consequently, the structural reassignment is a recurring theme in heliannuol's family. Through a rigorous and comprehensive quantum chemical simulation of NMR parameters, encompassing an integrated ANN-PRA/DP4+ tandem approach, we intended to advance unexplored directions regarding the structure of the entire heliannuol family. Furthermore, we found that the size of the fused ring significantly influences the signals corresponding to the aromatic ring, making this discovery an excellent diagnostic tool for quickly determining the core structure of these compounds.

Globunoids A-D, undescribed bichalconoid and biflavanoids with α-glucosidase and α-amylase inhibitory activities from Knema globularia stems

A bichalconoid, globunoid A (1) and three biflavanones, globunoids B-D (2-4), previously undescribed, were isolated from the stems of Knema globularia, along with fourteen known analogues 5-18. The chemical structures of 1-4 were elucidated by the comprehensive spectroscopic analysis including UV, IR, HRESIMS, and NMR; the absolute configurations were determined based on their NOESY data, DP4+ statistical analysis, and ECD calculation. Up to now, compounds 2 and 3 represent the first 3,3″-linked biflavanone structures. Among the isolated compounds, 2, 3, and 2,3-dihydrocalodenin B (6) potently inhibited α-glucosidase and α-amylase activities, with IC50 values in the range 1.1-7.5 μM. Furthermore, the most active compound 6 was found to be a non-competitive inhibitor against these two enzymes.

The accuracy limit of chemical shift predictions for species in aqueous solution

Interpreting NMR experiments benefits from first-principles predictions of chemical shifts. Reaching the accuracy limit of theory is relevant for unambiguous structural analysis and dissecting theoretical approximations. Since accurate chemical shift measurements are based on using internal reference compounds such as trimethylsilylpropanesulfonate (DSS), a detailed comparison of experimental with theoretical data requires simultaneous consideration of both target and reference species ensembles in the same solvent environment. Here we show that ab initio molecular dynamics simulations to generate liquid-state ensembles of target and reference compounds, including explicitly their short-range solvation environments and combined with quantum-mechanical solvation models, allows for predicting highly accurate 1H (∼0.1-0.5 ppm) and aliphatic 13C (∼1.5 ppm) chemical shifts for aqueous solutions of the model compounds trimethylamine N-oxide (TMAO) and N-methylacetamide (NMA), referenced to DSS without any system-specific adjustments. This encompasses the two peptide bond conformations of NMA identified by NMR. The results are used to derive a general-purpose guideline set for predictive NMR chemical shift calculations of NMA in the liquid state and to identify artifacts of force field models. Accurate predictions are only obtained if a sufficient number of explicit water molecules is included in the quantum-mechanical calculations, disproving a purely electrostatic model of the solvent effect on chemical shifts.

DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation

DP4+ is one of the most popular methods for the structure elucidation of natural products using NMR calculations. While the method is simple and easy to implement, it requires a series of procedures that can be tedious, coupled with the fact that its computational demand can be high in certain cases. In this work, we made a substantial improvement to these limitations. First, we deeply explored the effect of molecular mechanics architecture on the DP4+ formalism (MM-DP4+). In addition, a Python applet (DP4+App) was developed to automate the entire process, requiring only the Gaussian NMR output files and a spreadsheet containing the experimental NMR data and labels. The script is designed to use the statistical parameters from the original 24 levels of theory (employing B3LYP/6-31G* geometries) and the new 36 levels explored in this work (over MMFF geometries). Furthermore, it enables the development of customizable methods using any desired level of theory, allowing for a free choice of test molecules.

Molecular docking, DFT studies, and anti-inflammatory evaluation of peshawaraquinone isolated from Fernandoa adenophylla

In recent years, there has been growing interest in exploring natural compounds with anti-inflammatory properties for potential therapeutic applications. This study focuses on investigating the anti-inflammatory potential of peshawaraquinone (PAQ), a compound isolated from Fernandoa adenophylla, which is known for its local use in pain relief. We aim to evaluate the efficacy of peshawaraquinone in both in vitro and in vivo models and gain insights into its mode of action. In the in vitro Human red blood cell (HRBC) assay, various concentrations of peshawaraquinone were tested for their ability to inhibit the hemolysis of red blood cells, a well-established indicator of anti-inflammatory activity. The results demonstrated a maximum percent inhibition of 79.69 at a concentration of 100 µM, indicating significant anti-inflammatory potential. Furthermore, the in vivo xylene-induced ear edema model was employed to assess the compound's efficacy in reducing inflammation. Xylene was topically applied to the ear to induce edema, and peshawaraquinone was administered to evaluate its inhibitory effects. The findings revealed a substantial 74.19% reduction in ear edema, accompanied by decreased ear thickness and histopathological improvements, such as inhibited cell infiltration and epidermal hyperplasia. To gain further insights into the compound's mechanism of action, density functional theory (DFT) calculations were performed to investigate its spectroscopic characteristics and geometric properties. Additionally, docking studies were conducted on key targets involved in inflammation, including COX-1 and COX-2. In conclusion, this study showcases the significant anti-inflammatory potential of peshawaraquinone, offering promising prospects for its use as a natural anti-inflammatory agent. The results from both in vitro and in vivo models, as well as the mechanistic insights gained from computational analyses, provide a solid basis for further exploration of peshawaraquinone's therapeutic applications.Communicated by Ramaswamy H. Sarma.

Charge delocalization and aromaticity of doubly reduced double-walled carbon nanohoops

Cycloparaphenylenes (CPPs) exhibit selective host capabilities, featuring the ability to incorporate smaller CPPs to form double-walled host-guest complexes. Moreover, CPPs can also be stabilized by global aromaticity under twofold oxidation or reduction, involving electronic conjugation along with the overall structural backbone. Herein we explore the structural modifications, bonding, electron delocalization and magnetic properties of doubly reduced double-walled CPP complexes with DFT methods, in the isolated and aggregate [n + 5]CPP⊃[n]CPP^2- (n = 5-8) species. Our results show that the hosts undergo structural, bonding and delocalization deformations towards quinoidal configurations and exhibit global long-ranged shielding cones similar to global aromatic free dianionic CPPs, accounting for charge delocalization on the outer nanohoops, whereas the guests preserve local aromatic benzenoid configurations, resulting in global and local aromatic circuits within the host-guest aggregate. This observation suggests that in multi-layered related species electronic delocalization will be retained at the outer structural surface. The aromaticity of the hosts is manifested in the strong upfield shifts of the guests ¹H-NMR signals. Hence, CPP complexes can be extended to doubly reduced species stabilized by global host aromaticity expanding our understanding of doubled-walled nanotubes at the nanoscale regime.

Novel asymmetrical azines appending 1,3,4-thiadiazole sulfonamide: synthesis, molecular structure analyses, in silico ADME, and cytotoxic effect†

Toward finding potential and novel anticancer agents, we designed and prepared novel differently substituted unsymmetrical azine-modified thiadiazole sulfonamide derivatives using the “combi-targeting approach”. An efficient procedure for synthesizing the designed compounds starts with 5-acetyl-3-N-(4-sulfamoylphenyl)-2-imino-1,3,4-thiadi-azoline 4. The E/Z configuration for compound 5 was investigated based on spectral analysis combined with quantum mechanical calculation applying the DFT-B3LYP method and 6-31G(d) basis set. The computational results found that the E isomer was energetically more favorable than the Z isomer by 2.21 kcal mol⁻¹. Moreover, ¹H and ¹³C chemical shifts for the E and Z isomers in DMSO were predicted using the GIAO-B3LYP/6-31G(d) computations and IEF-PCM solvation model. The computed chemical shifts for both isomers are consistent with those observed experimentally, indicating that they exist in the solution phase. Moreover, the E/Z configuration for the synthesized azines 7a–c, 9, 11, 13, 15a and 15b was also studied theoretically using the DFT-B3LYP/6-31G(d) calculations. In silico prediction for the biological activities was reported regarding the HOMO–LUMO energy gaps and molecular reactivity descriptors besides the ADMT/drug-likeness properties. The cytotoxic effect of the synthesized compounds has been assayed via the determination of their IC₅₀.

Toward finding potential and novel anticancer agents, we designed and prepared novel differently substituted unsymmetrical azine-modified thiadiazole sulfonamide derivatives using the “combi-targeting approach”.

Molecular networking-based discovery of anti-inflammatory chromene dimers from Melicope pteleifolia

With the aid of a feature-based molecular networking strategy, five undescribed C₂ and C₁ symmetric chromene dimers, namely, melptelchromenes A-E, were isolated from the leaves of Melicope pteleifolia. Four asymmetric dimers were found to be racemates and were resolved by chiral phase HPLC analyses. Their structures, including absolute configurations, were elucidated by HRMS, NMR spectroscopy, and quantum mechanical calculations of ECD spectra and NMR chemical shifts. Melptelchromenes A-D possess a unique ethylidene linkage via two 2H-chromene cores, while melptelchromene E represents the first example of a dimeric chromene featuring a 1,3-diarylbutan-1-ol moiety. Of these compounds, 6,6'-linked dimeric chromenes showed nitric oxide inhibitory activities on lipopolysaccharide-induced RAW 264 cells, and (-)- and (+)-melptelchromene E were the two most potent compounds (IC₅₀, 3.0 and 5.1 μM, respectively).

C7 Epimerization of Benzylidene-Protected β-d-Idopyranosides Brings Structural Insights into Idose Conformational Flexibility

Idose is unique among other aldohexoses because of its high conformational flexibility in solution. We herein show that benzylidene acetal-protected 3-O-acyl-β-d-idopyranosides undergo Lewis acid-catalyzed C7 epimerization with concomitant ⁴C₁ to ¹C₄ ring inversion. The reaction conditions and structural parameters for this transformation to occur have been thoroughly investigated through an extensive glycosylation study combined with NMR analyses, X-ray diffraction, and quantum molecular modeling. In addition to reporting a direct, β-stereoselective idosylation approach, our work brings fundamental structural insights into the conformational flexibility of idose.

Diterpenoid Constituents of Psiadia punctulata and Evaluation of Their Antimicrobial Activity

Sixteen diterpenes (1-16), along with 10 previously described compounds, including four flavonoids and six diterpenes, were isolated from the aerial parts of Psiadia punctulata growing in Saudi Arabia. The diterpene structures were elucidated using NMR spectroscopy and mass spectrometry data. Furthermore, a DFT/NMR procedure was used to suggest the relative configuration of several compounds. The labdane-derived skeletons, namely, ent-atisane, ent-beyerene, ent-trachylobane, and ent-kaurene, were identified. The extracts, fractions, and pure compounds were then tested against Staphylococcus aureus, Streptococcus mutans, Treponema denticola, and Lactobacillus plantarum. One diterpenoid, namely, psiadin, showed an additive effect with the antiseptic chlorhexidine, with a fractional inhibitory concentration index of less than 1. Additionally, psiadin showed a prospective inhibition activity for bacterial efflux pumps.

Cytotoxic Sesquiterpenoids from Ammoides atlantica Aerial Parts

Seven new terpenoids, namely, guaiane (1-4), eudesmane (5), and bisabolane (6) sesquiterpenoids and a furanone (7), were isolated from the aerial parts of Ammoides atlantica, a herbaceous plant growing in Algeria, together with eight known compounds. All metabolites were characterized by their 1D and 2D NMR and HRESIMS data. A combined DFT/NMR method was applied to study the relative configurations of 1-4, 6, and 7. All compounds, except 2, were assayed against MCF-7, A375, A549, HaCaT, and Jurkat cell lines. Compounds 8, 10, and 11 induced a dose-dependent reduction in cell viability with different potency on almost all cell lines used. The most active compounds, 8 and 10, were studied to assess their potential apoptotic effects and cell cycle inhibition.

Synthesis, Carbonic Anhydrase II/IX/XII Inhibition, DFT, and Molecular Docking Studies of Hydrazide-Sulfonamide Hybrids of 4-Methylsalicyl- and Acyl-Substituted Hydrazide

Carbonic anhydrases (CAs and EC 4.2.1.1) are the Zn²⁺ containing enzymes which catalyze the reversible hydration of CO₂ to carbonate and proton. If they are not functioning properly, it would lead towards many diseases including tumor. Synthesis of hydrazide-sulfonamide hybrids (19-36) was carried out by the reaction of aryl (10-11) and acyl (12-13) hydrazides with substituted sulfonyl chloride (14-18). Final product formation was confirmed by FT-IR, NMR, and EI-MS. Density functional theory (DFT) calculations were performed on all the synthesized compounds to get the ground-state geometries and compute NMR properties. NMR computations were in excellent agreement with the experimental NMR data. All the synthesized hydrazide-sulfonamide hybrids were in vitro evaluated against CA II, CA IX, and CA XII isozymes for their carbonic anhydrase inhibition activities. Among the entire series, only compounds 22, 32, and 36 were highly selective inhibitors of hCA IX and did not inhibit hCA XII. To investigate the binding affinity of these compounds, molecular docking studies of compounds 32 and 36 were carried out against both hCA IX and hCA XII. By using BioSolveIT's SeeSAR software, further studies to provide visual clues to binding affinity indicate that the structural elements that are responsible for this were also studied. The binding of these compounds with hCA IX was highly favorable (as expected) and in agreement with the experimental data.

Synthesis of Functionalized Thiophene Based Pyrazole Amides via Various Catalytic Approaches: Structural Features through Computational Applications and Nonlinear Optical Properties

In the present study, pyrazole-thiophene-based amide derivatives were synthesized by different methodologies. Here, 5-Bromothiophene carboxylic acid (2) was reacted with substituted, unsubstituted, and protected pyrazole to synthesize the amide. It was observed that unsubstituted amide (5-bromo-N-(5-methyl-1H-pyrazol-3-yl)thiophene-2-carboxamide (7) was obtained at a good yield of about 68 percent. The unsubstituted amide (7) was arylated through Pd (0)-catalyzed Suzuki–Miyaura cross-coupling, in the presence of tripotassium phosphate (K₃PO₄) as a base, and with 1,4-dioxane as a solvent. Moderate to good yields (66–81%) of newly synthesized derivatives were obtained. The geometry of the synthesized compounds (9a–9h) and other physical properties, like non-linear optical (NLO) properties, nuclear magnetic resonance (NMR), and other chemical reactivity descriptors, including the chemical hardness, electronic chemical potential, ionization potential, electron affinity, and electrophilicity index have also been calculated for the synthesized compounds. In this study, DFT calculations have been used to investigate the electronic structure of the synthesized compounds and to compute their NMR data. It was also observed that the computed NMR data manifested significant agreement with the experimental NMR results. Furthermore, compound (9f) exhibits a better non-linear optical response compared to all other compounds in the series. Based on frontier molecular orbital (FMO) analysis and the reactivity descriptors, compounds (9c) and (9h) were predicted to be the most chemically reactive, while (9d) was estimated to be the most stable among the examined series of compounds.

Aplydactylonins A-C, three new sesquiterpenes from the Vietnamese sea hare Aplysia dactylomela and their cytotoxicity

Aplydactylonins A-C (1-3), three new sesquiterpenes, were isolated from the Vietnamese sea hare Aplysia dactylomela. Their structures and absolute configurations were elucidated based on spectroscopic analysis, X-ray crystallography, and density functional theory (DFT) calculations of NMR and ECD data. Compound 2 exhibited cytotoxicity against HepG2, DU145 and A549 cells with respective IC₅₀ values of 4.08 ± 0.63, 38.64 ± 1.04 and 12.33 ± 0.95 µM. In addition, HepG2 cells treated with 5 μM compound 2 for 48 h showed a significant increase in early apoptotic cells (P < 0.05) and increased caspase 3 activity (P < 0.01). Moreover, compound 2 induced sub-G1 phase arrest in HepG2 cells.

Real-time prediction of 1H and 13C chemical shifts with DFT accuracy using a 3D graph neural network

Nuclear magnetic resonance (NMR) is one of the primary techniques used to elucidate the chemical structure, bonding, stereochemistry, and conformation of organic compounds. The distinct chemical shifts in an NMR spectrum depend upon each atom's local chemical environment and are influenced by both through-bond and through-space interactions with other atoms and functional groups. The in silico prediction of NMR chemical shifts using quantum mechanical (QM) calculations is now commonplace in aiding organic structural assignment since spectra can be computed for several candidate structures and then compared with experimental values to find the best possible match. However, the computational demands of calculating multiple structural- and stereo-isomers, each of which may typically exist as an ensemble of rapidly-interconverting conformations, are expensive. Additionally, the QM predictions themselves may lack sufficient accuracy to identify a correct structure. In this work, we address both of these shortcomings by developing a rapid machine learning (ML) protocol to predict ¹H and ¹³C chemical shifts through an efficient graph neural network (GNN) using 3D structures as input. Transfer learning with experimental data is used to improve the final prediction accuracy of a model trained using QM calculations. When tested on the CHESHIRE dataset, the proposed model predicts observed ¹³C chemical shifts with comparable accuracy to the best-performing DFT functionals (1.5 ppm) in around 1/6000 of the CPU time. An automated prediction webserver and graphical interface are accessible online at http://nova.chem.colostate.edu/cascade/. We further demonstrate the model in three applications: first, we use the model to decide the correct organic structure from candidates through experimental spectra, including complex stereoisomers; second, we automatically detect and revise incorrect chemical shift assignments in a popular NMR database, the NMRShiftDB; and third, we use NMR chemical shifts as descriptors for determination of the sites of electrophilic aromatic substitution.

From quantum chemical and experimental NMR data, a 3D graph neural network, CASCADE, has been developed to predict carbon and proton chemical shifts. Stereoisomers and conformers of organic molecules can be correctly distinguished.

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Revving up 13C NMR shielding predictions across chemical space: benchmarks for atoms-in-molecules kernel machine learning with new data for 134 kilo molecules

The requirement for accelerated and quantitatively accurate screening of nuclear magnetic resonance spectra across the small molecules chemical compound space is two-fold: (1) a robust ‘local’ machine learning (ML) strategy capturing the effect of the neighborhood on an atom’s ‘near-sighted’ property—chemical shielding; (2) an accurate reference dataset generated with a state-of-the-art first-principles method for training. Herein we report the QM9-NMR dataset comprising isotropic shielding of over 0.8 million C atoms in 134k molecules of the QM9 dataset in gas and five common solvent phases. Using these data for training, we present benchmark results for the prediction transferability of kernel-ridge regression models with popular local descriptors. Our best model, trained on 100k samples, accurately predicts isotropic shielding of 50k ‘hold-out’ atoms with a mean error of less than 1.9 ppm. For the rapid prediction of new query molecules, the models were trained on geometries from an inexpensive theory. Furthermore, by using a Δ-ML strategy, we quench the error below 1.4 ppm. Finally, we test the transferability on non-trivial benchmark sets that include benchmark molecules comprising 10–17 heavy atoms and drugs.

Total synthesis, isolation, surfactant properties, and biological evaluation of ananatosides and related macrodilactone-containing rhamnolipids

Rhamnolipids are a specific class of microbial surfactants, which hold great biotechnological and therapeutic potential. However, their exploitation at the industrial level is hampered because they are mainly produced by the opportunistic pathogen Pseudomonas aeruginosa. The non-human pathogenic bacterium Pantoea ananatis is an alternative producer of rhamnolipid-like metabolites containing glucose instead of rhamnose residues. Herein, we present the isolation, structural characterization, and total synthesis of ananatoside A, a 15-membered macrodilactone-containing glucolipid, and ananatoside B, its open-chain congener, from organic extracts of P. ananatis. Ananatoside A was synthesized through three alternative pathways involving either an intramolecular glycosylation, a chemical macrolactonization or a direct enzymatic transformation from ananatoside B. A series of diasteroisomerically pure (1→2), (1→3), and (1→4)-macrolactonized rhamnolipids were also synthesized through intramolecular glycosylation and their anomeric configurations as well as ring conformations were solved using molecular modeling in tandem with NMR studies. We show that ananatoside B is a more potent surfactant than its macrolide counterpart. We present evidence that macrolactonization of rhamnolipids enhances their cytotoxic and hemolytic potential, pointing towards a mechanism involving the formation of pores into the lipidic cell membrane. Lastly, we demonstrate that ananatoside A and ananatoside B as well as synthetic macrolactonized rhamnolipids can be perceived by the plant immune system, and that this sensing is more pronounced for a macrolide featuring a rhamnose moiety in its native 1 C 4 conformation. Altogether our results suggest that macrolactonization of glycolipids can dramatically interfere with their surfactant properties and biological activity.

Giffonins, Antioxidant Diarylheptanoids from Corylus avellana, and Their Ability to Prevent Oxidative Changes in Human Plasma Proteins

With the aim to explore the ability of diarylheptanoids to reduce oxidative changes in human plasma proteins, a phytochemical investigation of the MeOH extract of Corylus avellana leaves was perfomed. Analysis by LC-ESI/LTQOrbitrap/MS/MSⁿ guided the isolation of two new diarylheptanoid derivatives, giffonins W (1) and X (2). The structures 1 and 2 were assigned by analysis of NMR data combined with a QM (quantum mechanical)/NMR approach. The absolute configurations of 1 and 2 were established by analysis of electronic circular dichroism (ECD) spectra compared with the TDDFT-simulated curves. The antioxidant activity of the new and known giffonins was evaluated by inhibition of human plasma lipid peroxidation. Giffonins with the highest inhibitory activity were tested for their ability to reduce oxidation of thiol groups and carbonylation in plasma proteins, and some of them exhibited higher antioxidant activity than curcumin.

Discovery of a Secalonic Acid Derivative from Aspergillus aculeatus, an Endophyte of Rosa damascena Mill., Triggers Apoptosis in MDA-MB-231 Triple Negative Breast Cancer Cells

A new secalonic acid derivative, F-7 (1), was isolated from the endophytic Aspergillus aculeatus MBT 102, associated with Rosa damascena. The planar structure of 1 was established on the basis of 1D and 2D NMR and ESI-TOF-MS spectra. The relative configuration of 1 was determined applying a combined quantum mechanical/NMR approach and, afterward, the comparison of calculated and experimental electronic circular dichroism spectra determined the assignment of its absolute configuration. The compound possesses strong cytotoxic activity against triple negative breast cancer (TNBC) cells. It was found to induce apoptosis, as evidenced by scanning electron microscopy and phase contrast microscopy. Furthermore, flow cytometry analyses demonstrated that 1 induced mitochondrial damage and reactive oxygen species mediated apoptosis, arresting the G1 phase of the cells in a dose-dependent manner. Also, the compound causes significant microtubule disruption in TNBC cells. Subsequently, 1 restricted the cell migration leading to the concomitant increase in expression of cleaved caspase and PARP.

Bivariate Metal-Organic Frameworks with Tunable Spin-Crossover Properties

In this work, pyrazine (A), aminopyrazine (B), quinoxaline (C), and 5,6,7,8-tetrahydroquinoxaline (D) have been screened out among a large number of pyrazine derivatives to construct Hofmann-type metal-organic frameworks (MOFs) Fe(L)[M(CN)₄ ] (M=Pt, Pd) with similar 3D pillared-layer structures. X-ray single-crystal diffraction reveals that the alternate linkage between M and Fe^II ions through cyano bridges forms the 2D extended metal cyanide sheets, and ligands A-D acted as vertical columns to connect the 2D sheets to give 3D pillared-layer structures. Subsequently, a series of bivariate MOFs were constructed by pairwise combination of the four ligands A-D, which were confirmed by ¹ H NMR, PXRD, FTIR, and Raman spectroscopy. The results demonstrated that ligand size and crystallization rate play a dominant role in constructing bivariate Hofmann-type MOFs. More importantly, the spin-crossover (SCO) properties of the bivariate MOFs can be finely tuned by adjusting the proportion of the two pillared ligands in the 3D Hofmann-type structures. Remarkably, the spin transition temperatures, T_c ↑ and T_c ↓ of Fe(A)_x (B)_1-x [Pt(CN)₄ ] (x=0 to 1) can be adjusted from 239 to 254 K and from 248 to 284 K, respectively. Meanwhile, the width of the hysteresis loops can be widened from 9 to 30 K. Changing Pt to Pd, the hysteresis loops of Fe(A)_x (B)_1-x [Pd(CN)₄ ] can be tuned from 9 (T_c ↑=215 K, T_c ↓=206 K) to 24 K (T_c ↑=300 K, T_c ↓=276 K). This research provides wider implications in the development of advanced bistable materials, especially in precisely regulating SCO properties.

NMR Calculations with Quantum Methods: Development of New Tools for Structural Elucidation and Beyond

Structural elucidation is an important and challenging stage in the discovery of new organic molecules. Single-crystal X-ray analysis provides the most unquestionable results, though in practice the availability of suitable crystals limits its broad use. On the other hand, NMR spectroscopy has become the leading and universal technique to accomplish the task. Despite continuous advances in the field, the misinterpretation of NMR data is commonplace, evidenced by the large number of erroneous structures being published in top journals. Quantum calculations of NMR chemical shifts and scalar coupling constants emerged as ideal complements to facilitate the elucidation process when experimental NMR data is inconclusive. Since seminal reports demonstrated that affordable DFT methods provide NMR predictions accurate enough to differentiate among closely related isomers, the discipline has experienced substantial growth. The impact has been felt in different areas, and nowadays the results of such calculations are routinely seen in high impact literature.This Account describes our investigations in the field of quantum NMR calculations, focusing on the development of tools for structural elucidation and practical applications. We pioneered the use of artificial intelligence methods in the development of novel strategies of structural validation. Our first generation of trained artificial neural networks (ANNs) showed excellent ability to identify mistakes at the atom connectivity level, whereas the use of multidimensional pattern recognition pushed the performance to the stereochemical limit. In a conceptually different approach, we developed DP4+, an updated version of the DP4 probability used to determine the most likely structure among two or more candidates when one set of experimental data is available. Increasing the level of theory in NMR calculations and including unscaled data in the formalism improved the performance of the method, further validated to settle the configuration of challenging motifs such as spiroepoxides or Mosher's derivatives. One of the limitations of DP4+ is related to the relatively large computational cost involved in obtaining DFT-optimized geometries, which led to the development of a fast variant including the valuable information provided by coupling constants (J-DP4 method).These tools were explored to suggest the most probable structure of controversial natural or unnatural products originally misassigned, with some predictions further validated by synthesis (as in the case of pseudorubriflordilactone B). The possibility of predicting the structure of a natural product without requiring authentic sample was investigated in collaboration with Prof. Pilli (UNICAMP, Brazil) in the computer-guided total synthesis and stereochemical revisions of several natural products. Despite these advances, there remain considerable challenges, such as the case of configurational assessment of polar systems featuring multiple intramolecular hydrogen bonding interactions because of the poor energy predictions provided by most DFT methods. In our latest work, we tackle this problem by averaging the results provided by randomly generated ensembles, paving the way for a new paradigm in quantum NMR-assisted structural elucidation.

DFT/NMR Approach for the Configuration Assignment of Groups of Stereoisomers by the Combination and Comparison of Experimental and Predicted Sets of Data

Quantum mechanical/nuclear magnetic resonance (NMR) approaches are widely used for the configuration assignment of organic compounds generally comparing one cluster of experimentally determined data (e.g., 13C NMR chemical shifts) with those predicted for all possible theoretical stereoisomers. More than one set of experimental data, each related to a specific stereoisomer, may occur in some cases, and the accurate stereoassignments can be obtained by combining the experimental and computed data. We introduce here a straightforward methodology based on the simultaneous analysis, combination, and comparison of all sets of experimental/calculated 13C chemical shifts for aiding the correct configuration assignment of groups of stereoisomers. The comparison of the differences between the calculated/experimental chemical shifts instead of the shifts themselves led to the advantage of avoiding errors arising from calibration procedures, reducing systematic errors, and highlighting the most diagnostic differences between calculated and experimental data. This methodology was applied on a tetrad of synthesized cladosporin stereoisomers (cladologs) and further corroborated on a tetrad of pochonicine stereoisomers, obtaining the correct correspondences between experimental and calculated sets of data. The new MAEΔΔδ parameter, useful for indicating the best fit between sets of experimental and calculated data, is here introduced for facilitating the stereochemical assignment of groups of stereoisomers.

The 6π-azaelectrocyclization of azatrienes. Synthetic applications in natural products, bioactive heterocycles, and related fields

Covering: 2006 to 2018 The application of the 6π-azaelectrocyclization of azatrienes as a key strategy for the synthesis of natural products, their analogs and related bioactive or biomedically-relevant compounds (from 2006 to date) is comprehensively reviewed. Details about reaction optimization studies, relevant reaction mechanisms and conditions are also discussed.

Isolation, Synthesis And Structure Determination Of Cannabidiol Derivatives And Their Cytotoxic Activities

In a continuing effort to explore the structural diversity and pharmacological activities of natural products based scaffolds, herein, we report the isolation, synthesis, and structure determination of cannabidiol and its derivatives along with their cytotoxic activities. Treatment of cannabidiol (1) with acid catalyst POCl₃ afforded a new derivative 6 along with six known molecules 2 - 5, 7 and, 8. The structure of 6 was elucidated by extensive spectroscopic analyses and DFT calculations of the NMR and ECD data. All the compounds (2 - 8) were evaluated for their cytotoxic potential against a panel of eight cancer cell lines. Compounds 4, 5, 7, and 8 showed pronounced in vitro cytotoxic activity with IC₅₀ values ranging from 5.6 to 60 μM. Out of the active molecules, compounds 4, and 7 were found to be comparable to that of the parent molecule 1 on the inhibition of almost all the tested cancer cell lines.

Immunomodulatory Biscembranoids and Assignment of Their Relative and Absolute Configurations: Data Set Modulation in the Density Functional Theory/Nuclear Magnetic Resonance Approach

Five new biscembranoids, bistrochelides A-E (3-7), were isolated together with glaucumolides A (1) and B (2) from the soft coral Sarcophyton trocheliophorum. Their structures and absolute configurations were determined by spectroscopic methods, X-ray crystal diffraction, and DFT/NMR (density functional theory/nuclear magnetic resonance) and TDDFT/ECD (time-dependent density functional theory/electronic circular dichroism) calculations. A new approach is introduced to determine the relative configuration of a stereocenter through the dynamic evaluation of the mean absolute errors (MAEs) between the investigated diastereoisomers, moving from an "extended" to a more diagnostic "restricted" set of atoms. This research leads to the structure revision of glaucumolides A and B. In in vitro immunomodulatory screening, compounds 1 and 4 significantly induced the proliferation of CD3⁺ T cells, while compounds 1 and 5 significantly increased the CD4⁺/CD8⁺ ratio at 3 μM.

Computationally-assisted discovery and structure elucidation of natural products

Computer hardware development coupled with the development of quantum chemistry, new computational models and algorithms, and user-friendly interfaces have lowered the barriers to the use of computation in the discovery and structure elucidation of natural products. Consequently, the use of computational chemistry software as a tool to discover and determine the structure of natural products has become more common in recent years. In this review, we provide several examples of recent studies that used computer technology to facilitate the discovery and structure determination of various natural products.

Computational Prediction of 1 H and 13 C NMR Chemical Shifts for Protonated Alkylpyrroles: Electron Correlation and Not Solvation is the Salvation

Prediction of chemical shifts in organic cations is known to be a challenge. In this article we meet this challenge for α-protonated alkylpyrroles, a class of compounds not yet studied in this context, and present a combined experimental and theoretical study of the ¹³ C and ¹ H chemical shifts in three selected pyrroles. We have investigated the importance of the solvation model, basis set, and quantum chemical method with the goal of developing a simple computational protocol, which allows prediction of ¹³ C and ¹ H chemical shifts with sufficient accuracy for identifying such compounds in mixtures. We find that density functional theory with the B3LYP functional is not sufficient for reproducing all ¹³ C chemical shifts, whereas already the simplest correlated wave function model, Møller-Plesset perturbation theory (MP2), leads to almost perfect agreement with the experimental data. Treatment of solvent effects generally improves the agreement with experiment to some extent and can in most cases be accomplished by a simple polarizable continuum model. The only exception is the NH proton, which requires inclusion of explicit solvent molecules in the calculation.

An automated framework for NMR chemical shift calculations of small organic molecules

When using nuclear magnetic resonance (NMR) to assist in chemical identification in complex samples, researchers commonly rely on databases for chemical shift spectra. However, authentic standards are typically depended upon to build libraries experimentally. Considering complex biological samples, such as blood and soil, the entirety of NMR spectra required for all possible compounds would be infeasible to ascertain due to limitations of available standards and experimental processing time. As an alternative, we introduce the in silico Chemical Library Engine (ISiCLE) NMR chemical shift module to accurately and automatically calculate NMR chemical shifts of small organic molecules through use of quantum chemical calculations. ISiCLE performs density functional theory (DFT)-based calculations for predicting chemical properties—specifically NMR chemical shifts in this manuscript—via the open source, high-performance computational chemistry software, NWChem. ISiCLE calculates the NMR chemical shifts of sets of molecules using any available combination of DFT method, solvent, and NMR-active nuclei, using both user-selected reference compounds and/or linear regression methods. Calculated NMR chemical shifts are provided to the user for each molecule, along with comparisons with respect to a number of metrics commonly used in the literature. Here, we demonstrate ISiCLE using a set of 312 molecules, ranging in size up to 90 carbon atoms. For each, calculation of NMR chemical shifts have been performed with 8 different levels of DFT theory, and with solvation effects using the implicit solvent Conductor-like Screening Model. The DFT method dependence of the calculated chemical shifts have been systematically investigated through benchmarking and subsequently compared to experimental data available in the literature. Furthermore, ISiCLE has been applied to a set of 80 methylcyclohexane conformers, combined via Boltzmann weighting and compared to experimental values. We demonstrate that our protocol shows promise in the automation of chemical shift calculations and, ultimately, the expansion of chemical shift libraries.

Method Calibration or Data Fitting?

We investigate by explicit parameter optimization to what extent basis sets of polarized double-ζ quality can introduce compensating errors in five different density functional methods. It is shown that minor changes in the contraction coefficients of the valence functions in the basis sets can have a significant impact and allow different density functional methods to achieve very similar performances. This holds for nuclear magnetic shielding constants and for isomerization energies, barrier heights, and noncovalent interactions. It is furthermore shown that errors due to neglect of vibrational and solvent effects can be absorbed in the combined method and basis set errors. These findings hold for data sets consisting of 50-150 data points. This raises the question of whether the common practice of identifying combinations of density functional methods and basis sets that have a good performance against a selected set of reference data should be considered as data fitting in the combined parameter space spanned by the method and basis set.

Glucopyranosylbianthrones from the Algerian Asphodelus tenuifolius: Structural Insights and Biological Evaluation on Melanoma Cancer Cells

Two new glucopyranosylbianthrones (1 and 2) were isolated from the aerial part of the plant Asphodelus tenuifolius, collected in Southwest Algeria. The 2D structures of 1 and 2 were defined by NMR analysis, HRESIMS data, and comparison with literature data. The comparison of experimental and calculated electronic circular dichroism and NMR data led to characterization of the ( M) and ( P) atropisomeric forms of the glucopyranosylbianthrones, asphodelins (1) and (2), respectively. The in vitro activities of these two metabolites were evaluated in human melanoma A375 cells, and both the compounds inhibited cell proliferation in a concentration-dependent manner, with IC₅₀ values of 20.6 ± 0.8 and 23.2 ± 1.1 μM, respectively. Considering their biological profile, an inverse virtual screening approach was employed to identify and suggest putative anticancer interacting targets.

Synthesis and characterisation of fluorescent aminophosphines and their coordination to gold(i)

Three novel fluorescent aminophosphine ligands have been synthesised that incorporate napthyl (L1), pyrenyl (L2) and anthraquinone (L3) chromophores into their structures. The ligands react with [AuCl(tht)] (tht = tetrahydrothiophene) to give neutral complexes of the form [AuCl(L1-3)]. Solid state, X-ray crystallographic data was obtained for the anthraquinone derivative, [AuCl(L3)], and showed a distorted linear coordination geometry at Au(i). The packing structure also revealed a number of intermolecular π-π interactions that involve the anthraquinone and phenyl units of the aminophosphine ligand. 31P NMR spectroscopic data revealed δP values of +42.2 (L1), +42.1 (L2) and +26.1 (L3) ppm, which shifted downfield upon coordination to Au(i) to +64.6, +64.7, and +55.8 ppm, respectively. Supporting TD-DFT studies were able to reproduce the structure and 31P NMR chemical shifts of [AuCl(L3)] as well as rationalise the HOMO-LUMO compositions. Photophysical studies showed that the appended fluorophore dominates the absorption and emission properties for the ligands and complexes, with the anthraquinone derivatives showing visible emission at ca. 570 nm which was attributed to the intramolecular charge transfer character of the phosphinoaminoanthraquinone fragment.

Prediction of 1H NMR chemical shifts for ionic liquids: strategy and application of a relative reference standard

The computational predictions of ¹H NMR chemical shifts for ionic liquids were investigated. To calculate the chemical shifts more accurately, the approach of relative reference standard (RRS) was proposed. This straightforward computational technique uses organic compounds and ionic liquids that are similar to the studied ionic liquids as standards. The calculated chemical shifts of single ion pairs were strongly influenced by the anion type and the local environment. Using the RRS methodology, the calculated results agreed well with the experimental chemical shifts due to the cancellation of errors caused by the anion. Ionic clusters consisting of 4 ion pairs were also employed to model the ionic liquids with strongly coordinating anions. Large clusters slightly improve the accuracy by reducing systematic errors. Although the experimental ¹H NMR data of the reference ionic liquid should be used, the RRS methodology has been shown to predict ¹H NMR chemical shifts efficiently at different levels of theory.

Using an RRS method to calculate the ¹H NMR chemical shifts of ionic liquid agreed well with the experimental value.

NMR and experimental reinvestigation of the condensation reaction between γ-methylene-α,β-unsaturated aldehydes and propargyl aldehydes

An experimental and computational study of the reaction between γ-methylene enals and propargyl aldehydes uncovered a deconjugative aldol condensation.

Ring-Fused Cyclic Aminals from Tetrahydro-β-carboline-Based Dipeptide Compounds

An acid- and oxidant-promoted intramolecular cyclization of a tetrahydro-β-carboline-based dipeptide has been developed to prepare new indole-fused aminoacetals. This approach involves N-acyliminium formation from readily available precursors and cyclization under mild reaction conditions. The diastereoselectivity in the formation of the products is influenced by the specific substituents of the starting reagents, which has been rationalized analyzing the energy profile of the related reactions and the relative stability of the proposed structures based on DFT computational methods.

A molecular mechanics and ab initio prediction of the 1 H chemical shifts of pinanes

Molecular mechanics calculations plus the application of a refined Karplus equation gave the conformations of 19 pinanes. These range from a Y-shaped geometry in the apopinene and α-pinene series to a pseudo chair conformation in β-pinene, nopinone and verbanone, a flattened chair in pinocarvone and the pinocarveols and a distorted Y shape for iso-verbanone. These structures were then used as input to predict the ¹ H chemical shifts of these compounds by semi-empirical (¹ H-NMR spectra (HSPEC)) and ab initio gauge-invariant atomic orbital (GIAO) calculations, the latter at the B3LYP hybrid density functional theory level using 6-31++G** basis set. The two methods gave generally good agreement with the 184 observed shifts with root mean square (RMS) errors 0.07 ppm (HSPEC) and 0.10 ppm (GIAO), but the GIAO calculations gave several significant (>0.25 ppm) errors. One was for the H₃ proton in apopinenone and other α,β unsaturated ketones; the others occurred for protons in close proximity to hydroxyl groups. To provide more information, smaller analogues of known geometry and chemical shifts were subject to the same analysis. In cyclopentenone, the Gaussian geometry gave good agreement with the observed shifts, but the MMFF94, MMX and MM3 geometries all gave errors for different protons. These results show clearly that the molecular geometries of the α,β unsaturated ketones are responsible for the errors. The errors for the alcohols were examined using ethanol as model and were shown to be due to the different possible conformations of the OH group. Similar GIAO calculations on substituted methanes gave good agreement for the methyl compounds but poor agreement for di and tri halosubstituted methanes. The aforementioned method of molecular mechanics plus GIAO calculations is shown to be a very useful tool for the investigation of molecular geometries and conformations. However, multihalogen compounds may require different basis sets for accurate calculations. Copyright © 2017 John Wiley & Sons, Ltd.

Cyclic Diarylheptanoids from Corylus avellana Green Leafy Covers: Determination of Their Absolute Configurations and Evaluation of Their Antioxidant and Antimicrobial Activities

The methanol extract of the leafy covers of Corylus avellana, source of the Italian PGI (protected geographical indication) product "Nocciola di Giffoni", afforded two new cyclic diarylheptanoids, giffonins T and U (2 and 3), along with two known cyclic diarylheptanoids, a quinic acid, flavonoid-, and citric acid derivatives. The structures of giffonins T and U were determined as highly hydroxylated cyclic diarylheptanoids by 1D and 2D NMR experiments. Their relative configurations were assigned by a combined quantum mechanical/NMR approach, comparing the experimental ¹³C/¹H NMR chemical shift data and the related predicted values. The absolute configurations of carpinontriol B (1) and giffonins T and U (2 and 3) were assigned by comparison of their experimental electronic circular dichroism curves with the TDDFT-predicted curves. The ability of the compounds to inhibit the lipid peroxidation induced by H₂O₂ and H₂O₂/Fe²⁺ was determined by measuring the concentration of thiobarbituric acid reactive substances. Furthermore, the antimicrobial activity of the methanol extract of leafy covers of C. avellana and of the isolated compounds against the Gram-positive strains Bacillus cereus and Staphylococcus aureus and the Gram-negative strains Escherichia coli and Pseudomonas aeruginosa was evaluated. Carpinontriol B (1) and giffonin U (3) at 40 μg/disk caused the formation of zones of inhibition.

Svetamycins A-G, Unusual Piperazic Acid-Containing Peptides from Streptomyces sp

Seven new halogenated peptides termed svetamycins A-G (1-7) have been isolated from laboratory cultures of a Streptomyces sp. Svetamycins A-D, F, and G are cyclic depsipeptides, whereas svetamycin E is a linear analogue of svetamycin C. Their structures were determined using extensive spectroscopic analysis, and their stereochemical configuration was established by a combination of NMR data, quantum mechanical calculations, and chemical derivatizations. Svetamycins are characterized by the presence of a hydroxyl acetic acid and five amino acids including a rare 4,5-dihydroxy-2,3,4,5-tetrahydropyridazine-3-carboxylic acid, a γ-halogenated piperazic acid, and a novel δ-methylated piperazic acid in svetamycins B-C, E, and G. Moreover, isotope-labeled substrate feeding experiments demonstrated ornithine as the precursor of piperazic acid and that methylation at the δ position of the piperazyl scaffold is S-adenosyl-l-methionine (SAM)-dependent. Svetamycin G, the most potent antimicrobial of this suite of compounds, inhibited the growth of Mycobacterium smegmatis with an MIC₈₀ value of 2 μg/mL.