Spectroscopic Patterns Research Articles

Robust 1D selective correlation NMR spectroscopy for rapid chemical and biological applications

Selective homonuclear proton correlation NMR spectroscopy (COSY) provides a useful detection tool for elucidating molecular structures and identifying chemical compositions in 1D spectroscopic patterns. However, conventional 1D selective COSY experiments highly rely on the performance of selective excitation on targeted signals and their applications generally suffer from spectral congestion in complex chemical and biological samples. Herein, based on the concept of targeted excitation on coupled proton pairs and spectroscopic separation on their respective COSY responses, we propose a 1D selective NMR approach that is capable of individually recording direct coupling correlation information of targeted proton groups for analyses on complex samples, free of spectral congestion. The performance of the proposed approach is demonstrated on a medicine sample, a biological molecule, and a real metabonomics sample of human serum. This approach shows a promising analytical technique for structural studies and component analyses in chemical and biological applications. Keywords: NMR spectroscopy, Correlation spectroscopy, Targeted signal excitation, Spectral congestion, Molecular structure analysis.

Investigation of Anisotropic Electronic Structure in Graphite by Momentum-Resolved Electron Energy Loss Spectroscopy (ω-q Mapping) and Electron Spectroscopic Diffraction Patterns

Investigation of Anisotropic Electronic Structure in Graphite by Momentum-Resolved Electron Energy Loss Spectroscopy (<i>ω</i>-<i>q</i> Mapping) and Electron Spectroscopic Diffraction Patterns

Deep learning-based Raman spectroscopy qualitative analysis algorithm: A convolutional neural network and transformer approach

Raman spectroscopy is a general and non-destructive detection technique that can obtain detailed information of the chemical structure of materials. In the past, when using chemometric algorithms to analyze the Raman spectra of mixtures, the challenges of complex spectral overlap and noise often limited the accurate identification of components. The emergence of deep learning has introduced a novel approach to qualitative analysis of mixed Raman spectra. In this paper, we propose a deep learning-based Raman spectroscopy qualitative analysis algorithm (RST) by borrowing the ideas of convolutional neural network and Transformer. By transforming the Raman spectrum into 64 word vectors, the contribution weights of each word vector to the components are obtained. For the 75 spectral data used for validation, the positive identification rate can reach 100.00 %, the recall rate can reach 99.3 %, the average identification score can reach 9.51, and it is applicable to the fields of Raman and surface-enhanced Raman spectroscopy. Furthermore, compared with traditional CNN models, RST has excellent accuracy and robustness in identifying components in complex mixtures. The model's interpretability has been enhanced, aiding in a deeper understanding of spectroscopic learning patterns for future analysis of more complex mixtures.

Topological characterizations on hexagonal and rectangular tessellations of antikekulenes and its computed spectral, nuclear magnetic resonance and electron spin resonance characterizations

AbstractTessellations of antikekulenes are of interest from the standpoints of antiaromaticity, ring currents, unusual ‐electron characteristics, magnetism and their highly reactive nature. Although precursors of antikekulenes have been synthesized, up to now synthesis of antikekulenes has been proven to be formidably difficult. Yet they are predicted to have intriguing properties and their antiaromatic nature together with a combination of four and six‐membered rings makes them intriguing candidates for theoretical indices. In the present study, we have computed the topological indices of antikekulene by employing graph‐theoretical cut methods that simplify the parent tessellations of antikekulenes into simpler graphs. We have derived exact mathematical expressions of several topological descriptors for hexagonal and rectangular antikekulene structures. Furthermore we have obtained the graph‐spectral properties, algebraic structure counts, resonance stabilization and delocalization energies as well as nuclear magnetic resonance and electron spin resonance spectroscopic patterns of the two tessellations of antikekulenes.

Cuticle chemistry of the Cheirolepidiaceae Frenelopsis teixeirae from the Lower Cretaceous of Portugal. A case of study using ATR-FTIR spectroscopy

A Cheirolepidiaceae Frenelopsis teixeirae from the Lower Cretaceous of the Santa Susana Formation, near Torres Vedras locality (Estremadura region, western Portugal), is analyzed by means of Fourier Transform Infrared (FTIR) spectroscopy in Attenuated Total Reflection (ATR) mode at both micro and macro scales. This analytical technique (ATR-FTIR spectroscopy), which requires minimal sample preparation and a small amount of material, is used to evaluate the chemical composition of the F. teixeirae cuticles. For this, functional groups (i.e., specific groupings of atoms within molecules), that compose the complex chemical structure making up the F. teixeirae cuticles, are detected, analyzed, and interpreted from the resulting spectra. The Frenelopsis material comprises compressions of eighteen leafy axes with very well-preserved cuticles. Previously reported chemical information derived from transmission FTIR spectra of the foliar cuticle of the podocarp Squamastrobus tigrensis from the Lower Cretaceous of Argentina is used for comparison in order to assess the existence of a distinctive spectroscopic pattern for this Portuguese taxon. Semi-quantitative data derived from FTIR spectra of both fossil taxa were statistically analyzed using principal component analysis (PCA). The F. teixeirae cuticles have a lower contribution of C=O stretch and a lower degree of biopolymeric matrix cross-linking (higher CHal/C=O ratio) than those of S. tigrensis. Despite the existing differences between both conifers, spectroscopic patterns characterizing each fossil taxon are not fully distinctive from a chemotaxonomic perspective. This is mainly related to the relatively variable morphological cuticular features (e.g., trichomes) and to the biomacropolymeric chemistry among the leaves of each fossil taxon.

Biosynthesis and physicochemical properties of low molecular weight gellan produced by a high-yield mutant of Sphingomonas paucimobilis ATCC 31461

Gellan gum (GG) is used in many industries. Here, we obtained a low molecular weight GG (L-GG) directly produced by M155, the high-yield mutant strain of Sphingomonas paucimobilis ATCC 31461, which was selected using UV-ARTP combined mutagenesis. The molecular weight of L-GG was 44.6 % lesser than that of the initial GG (I-GG), and the GG yield increased by 24 %. The monosaccharide composition and Fourier transform-infrared spectroscopic patterns of L-GG were similar to those of I-GG, which indicated that the decrease in the molecular weight of L-GG was probably because of reduction in the degree of polymerization. In addition, microstructural analysis revealed that the surface of L-GG was rougher, with smaller pores and tighter network, than that of I-GG. L-GG showed low hardness, gumminess, and chewiness, which are indicative of better taste. The results of rheological analysis revealed that the L-GG solution is a typical non-Newtonian fluid with low viscoelasticity, which exhibited stable dynamic viscoelasticity within 20–65 °C. To the best of our knowledge, this is the first report of direct biosynthesis of low molecular weight GG during fermentation, which will reduce the manufacturing costs. Our observations provide a reference for precise and expanded applications of GG.

Shock wave recovery experiments on poly-crystalline tri-glycine sulfate – X-ray and Raman analyses

Recent reports of shock wave experiments on non-linear optical (NLO) crystals have demonstrated outstanding results. Suitable candidates are currently being studied for industrial applications. For the present experiment, we have chosen tri-glycine sulfate (TGS) for the investigation of the structural properties after shock wave loaded conditions by employing X-ray diffraction and Raman spectroscopic measurements. The observed diffraction and spectroscopic patterns of the test polycrystalline sample reveal that the test sample does not undergo any crystallographic phase transition. But, there are several additional shoulder peaks observed and Raman measurements show that a few Raman bands appear while some disappear by the impact of shock waves due to the re-orientational effect of glycine molecules. The observed interesting results are discussed.

A comparative study of adsorption behavior of rifampicin, streptomycin, and ibuprofen contaminants from aqueous solutions onto chitosan: Dynamic interactions, kinetics, diffusions, and mechanisms

Adsorptive removal and dynamic interaction of three different pharmaceutical pollutants, namely rifampicin (RIF), streptomycin (STM), and ibuprofen (IBU) onto chitosan were systematically investigated using a batch adsorption technique at different processing parameters. In this study, chitosan was derived from mud-crab shells, as an innovative way to use the waste from marine foods as adsorbents. The kinetics, intraparticle diffusion, mechanism, and thermodynamics of the adsorption were systematically evaluated and analyzed using kinetic models, Boyd mass transfer and Weber–Morris intraparticle diffusion models, Langmuir, Freundlich, Dubinin–Radushkevich, and Temkin isotherm models, and the Gibbs equation. The adsorption isotherm of the larger molecules, RIF and STM, could be explained by the Langmuir isotherm model, in contrast, that of IBU, which is a much smaller molecule, followed the Freundlich isotherm model. The maximum adsorption capacity of RIF, STM, and IBU on chitosan was estimated to be 66.91 mg g−1, 11.00 mg g−1, and 24.21 mg g−1, respectively, which are higher compared to those on a variety of agricultural wastes, suggesting that this biopolymer is a potential practical and economical adsorbent to remove the pharmaceutical compounds from wastewater. The adsorption mechanism of the pharmaceutical compounds on chitosan is proposed based on the vibrational spectroscopic analyses, XRD patterns, and DSC thermograms of the biopolymer before and after adsorption process.

Lower Posterior Cingulate N-Acetylaspartate to Creatine Level in Early Detection of Biologically Defined Alzheimer's Disease.

Alzheimer’s disease (AD) was recently defined as a biological construct to reflect neuropathologic status, and both abnormal amyloid and tau are required for a diagnosis of AD. We aimed to determine the proton MR spectroscopic (1H-MRS) patterns of the posterior cingulate in biologically defined AD. A total of 68 participants were included in this study, comprising 37 controls, 16 early AD, and 15 late AD, who were classified according to their amyloid and tau status and presence of hippocampal atrophy. Compared with controls, early AD showed lower N-acetylaspartate (NAA)/creatine (Cr) (p = 0.003), whereas late AD showed lower NAA/Cr and higher myoInositol (mI)/Cr (all with p < 0.05). Lower NAA/Cr correlated with a greater global amyloid load (r = −0.47, p < 0.001) and tau load (r = −0.51, p < 0.001) and allowed a discrimination of early AD from controls (p < 0.001). Subgroup analysis showed that NAA/Cr also allowed a differentiation of early AD from controls in the cognitively unimpaired subjects, with an area under the receiver operating characteristics curve, sensitivity, and specificity of 0.96, 100%, and 83.8%, respectively. Lower posterior cingulate NAA levels may help to inform underlying neuropathologic changes in the early stage of AD.

Two-dimensional coronene fractal structures: topological entropy measures, energetics, NMR and ESR spectroscopic patterns and existence of isentropic structures

Molecular fractals are geometric patterns that appear self-similar across all length scales and are constructed by repeating a single unit on a regular basis. The benzenoid compounds are found to have a natural pattern that helps to analyse and explore the potential attributes of these molecular fractals. Here, we focus on coronene-based fractals where coronene is a benzenoid molecule with a symmetric graphite-like structure and challenging synthesis methods. Topological molecular descriptors are obtained in order to provide structure-activity relations for the physico-chemical properties. We obtain these descriptors for the molecular fractals that are constructed by repeating a fixed unit of coronene on different stages systematically. The structural characterisation of the two-dimensional coronene fractals in various tessellations is presented through a wide range of degree-based topological indices. The entropy measures of these significant frameworks are also computed for estimating their potential attributes, and the comparison of their values among various degree-based indices is performed, which shows the existence of isentropic structures. We have developed machine learning techniques for robust computations of the enthalpies, NMR and ESR spectroscopic patterns of coronene fractals.

Production, Bioprocessing and Anti-Proliferative Activity of Camptothecin from Penicillium chrysogenum, "An Endozoic of Marine Sponge, Cliona sp.", as a Metabolically Stable Camptothecin Producing Isolate.

Exploring the metabolic potency of fungi as camptothecin producers raises the hope of their usage as an industrial source of camptothecin, due to their short-life span and the feasibility of metabolic engineering. However, the tiny yield and loss of camptothecin productivity of fungi during storage and sub-culturing are challenges that counteract this approach. Marine fungi could be a novel source for camptothecin production, with higher yield and reliable metabolic sustainability. The marine fungal isolate Penicillium chrysogenum EFBL # OL597937.1 derived from the sponge “Cliona sp.” has been morphologically identified and molecularly confirmed, based on the Internal Transcribed Spacer sequence, exhibiting the highest yield of camptothecin (110 μg/L). The molecular structure and chemical identity of P. chrysogenum derived camptothecin has been resolved by HPLC, FTIR and LC-MS/MS analyses, giving the same spectroscopic profiles and mass fragmentation patterns as authentic camptothecin. The extracted camptothecin displayed a strong anti-proliferative activity towards HEP-2 and HCT-116 (IC50 values 0.33–0.35 µM). The yield of camptothecin was maximized by nutritional optimization of P. chrysogenum with a Plackett-Burman design, and the productivity of camptothecin increased by 1.8 fold (200 µg/L), compared to control fungal cultures. Upon storage at 4 °C as slope culture for 8 months, the productivity of camptothecin for P. chrysogenum was reduced by 40% compared to the initial culture. Visual fading of the mycelial pigmentation of P. chrysogenum was observed during fungal storage, matched with loss of camptothecin productivity. Methylene chloride extracts of Cliona sp. had the potency to completely restore the camptothecin productivity of P. chrysogenum, ensuring the partial dependence of the expression of the camptothecin biosynthetic machinery of P. chrysogenum on the chemical signals derived from the sponge, or the associated microbial flora. This is the first report describing the feasibility of P. chrysogenum, endozoic of Cliona sp., for camptothecin production, along with reliable metabolic biosynthetic stability, which could be a new platform for scaling-up camptothecin production.

Molecular formations and spectra due to electron correlations in three-electron hybrid double-well qubits

We show that systematic full configuration-interaction (FCI) calculations enable prediction of the energy spectra and the intrinsic spatial and spin structures of the many-body wave functions as a function of the detuning parameter for the case of three-electron hybrid qubits based on GaAs asymmetric double quantum dots. Specifically, in comparison with the case of weak interactions and treating the entire three-electron double-dot hybrid qubit as an integral unit, it is shown that the predicted spectroscopic patterns, originating from strong electron correlations, manifest the formation of Wigner molecules (WMs). Signatures of WM formation include: (1) a strong suppression of the energy gaps relative to the non-interacting-electrons modeling, and (2) the appearance of a pair of avoided crossings arising between states associated with two-electron occupancies in the left and right wells. The Wigner molecule is a physical entity associated with electron localization within each well and it cannot be captured by the previously employed independent-particle or two-site-Hubbard theoretical modeling of the hybrid qubits. The emergence of strong WMs is investigated in depth through the concerted use of FCI-adapted diagnostic tools like charge and spin densities, as well as conditional probability distributions. Furthermore, the energy spectrum as a function of the strength of the Coulomb repulsion (at constant detuning) is calculated in order to complement the thorough analysis of the factors contributing to WM emergence. We report remarkable agreement with recent experimental measurements. The present FCI methodology for multi-well quantum dots can be straightforwardly extended to treat valleytronic two-band Si/SiGe hybrid qubits, where the central role of the WMs was confirmed recently.

Wigner molecules and hybrid qubits

It is demonstrated that exact diagonalization of the microscopic many-body Hamiltonian via systematic full configuration-interaction (FCI) calculations is able to predict the spectra as a function of detuning of three-electron hybrid qubits based on GaAs asymmetric double quantum dots (QDs). It is further shown that, as a result of strong inter-electron correlations, these spectroscopic patterns, including avoided crossings between states associated with different electron occupancies of the left and right wells, are inextricably related to the formation of Wigner molecules (WMs). These physical entities cannot be captured by the previously employed independent-particle or Hubbard-type theoretical modeling of the hybrid qubit. We report remarkable agreement with recent experimental results. Moreover, the present FCI methodology for multi-well QDs can be straightforwardly extended to treat Si/SiGe hybrid qubits, where the central role of WMs was recently experimentally confirmed as well.

Detection of SARS-CoV-2 infection by exhaled breath spectral analysis: Introducing a ready-to-use point-of-care mass screening method.

SummaryBackgroundThe current SARS-CoV-2 pandemic created an urgent need for rapid, infection screening applied to large numbers of asymptomatic individuals. To date, nasal/throat swab polymerase chain reaction (PCR) is considered the “gold standard”. However, this is inconducive to mass, point-of-care (POC) testing due to person discomfort during sampling and a prolonged result turnaround. Breath testing for disease specific organic compounds potentially offers a practical, rapid, non-invasive, POC solution. The study compares the Breath of Health, Ltd. (BOH) breath analysis system to PCR's ability to screen asymptomatic individuals for SARS-CoV-2 infection. The BOH system is mobile and combines Fourier-transform infrared (FTIR) spectroscopy with artificial intelligence (AI) to generate results within 2 min and 15 s. In contrast to prior SARS-CoV-2 breath analysis research, this study focuses on diagnosing SARS-CoV-2 via disease specific spectrometric profiles rather than through identifying the disease specific molecules.MethodsAsymptomatic emergency room patients with suspected SARS-CoV-2 exposure in two leading Israeli hospitals were selected between February through April 2021. All were tested via nasal/throat-swab PCR and BOH breath analysis. In total, 297 patients were sampled (mean age 57·08 SD 18·86, 156 males, 139 females, 2 unknowns). Of these, 96 were PCR-positive (44 males, 50 females, 2 unknowns), 201 were PCR-negative (112 males, 89 females). One hundred samples were used for AI identification of SARS-CoV-2 distinguishing spectroscopic wave-number patterns and diagnostic algorithm creation. Algorithm validation was tested in 100 proof-of-concept samples (34 PCR-positive, 66 PCR-negative) by comparing PCR with AI algorithm-based breath-test results determined by a blinded medical expert. One hundred additional samples (12 true PCR-positive, 85 true PCR-negative, 3 confounder false PCR-positive [not included in the 297 total samples]) were evaluated by two blinded medical experts for further algorithm validation and inter-expert correlation.FindingsThe BOH system identified three distinguishing wave numbers for SARS-CoV-2 infection. In the first phase, the single expert identified the first 100 samples correctly, yielding a 1:1 FTIR/AI:PCR correlation. The two-expert second-phase also yielded 1:1 FTIR/AI:PCR correlation for 97 non-confounders and null correlation for the 3 confounders. Inter-expert correlation was 1:1 for all results. In total, the FTIR/AI algorithm demonstrated 100% sensitivity and specificity for SARS-CoV-2 detection when compared with PCR.InterpretationThe SARS-CoV-2 method of breath analysis via FTIR with AI-based algorithm demonstrated high PCR correlation in screening for asymptomatic individuals. This is the first practical, rapid, POC breath analysis solution with such high PCR correlation in asymptomatic individuals. Further validation is required with a larger sample size.FundingBreath of Health Ltd, Rehovot, Israel provided study funding.

Symmetry and Combinatorial Concepts for Cyclopolyarenes, Nanotubes and 2D-Sheets: Enumerations, Isomers, Structures Spectra &amp; Properties

This review article highlights recent developments in symmetry, combinatorics, topology, entropy, chirality, spectroscopy and thermochemistry pertinent to 2D and 1D nanomaterials such as circumscribed-cyclopolyarenes and their heterocyclic analogs, carbon and heteronanotubes and heteronano wires, as well as tessellations of cyclopolyarenes, for example, kekulenes, septulenes and octulenes. We establish that the generalization of Sheehan’s modification of Pólya’s theorem to all irreducible representations of point groups yields robust generating functions for the enumeration of chiral, achiral, position isomers, NMR, multiple quantum NMR and ESR hyperfine patterns. We also show distance, degree and graph entropy based topological measures combined with techniques for distance degree vector sequences, edge and vertex partitions of nanomaterials yield robust and powerful techniques for thermochemistry, bond energies and spectroscopic computations of these species. We have demonstrated the existence of isentropic tessellations of kekulenes which were further studied using combinatorial, topological and spectral techniques. The combinatorial generating functions obtained not only enumerate the chiral and achiral isomers but also aid in the machine construction of various spectroscopic and ESR hyperfine patterns of the nanomaterials that were considered in this review. Combinatorial and topological tools can become an integral part of robust machine learning techniques for rapid computation of the combinatorial library of isomers and their properties of nanomaterials. Future applications to metal organic frameworks and fullerene polymers are pointed out.

Photo-Triggered Chiroptical Switching of Platinum Complexes Bearing Azobenzene Moieties

l-Alanine-derived optically active trans-platinum complexes bearing azobenzene moieties, l-trans-Pt[P(Ph)2-1,4-C6H4-CONH-C*H(CH3)-CONH-1,4-C6H4-N═N-Ph]2(C≡CPh)2 (L-2a-5t) and l-cis-Pt[P(Ph)2-1,4-C6H4-CONH-C*H(CH2Ph)-CONH-1,4-C6H4-N═N-Ph]2(C≡CPh)2 (L-2a-5c) were synthesized by the ligand exchange reaction of trans-Pt(PPh3)2(C≡CPh)2 and cis-Pt(cod)(C≡CPh)2, respectively, with l-P(Ph)2-1,4-C6H4-CONH-C*H(CH2Ph)-CONH-1,4-C6H4-N═N-Ph. The trans-azobenzene moieties of the complexes isomerized to the cis form upon UV-light irradiation and returned to the trans form upon visible-light irradiation. L-2a-5t displayed weak circular dichroism (CD) signals irrespective of the trans and cis forms of the azobenzene moieties. On the other hand, L-2a-5c with trans-azobenzene moieties displayed strong CD signals, whose intensity decreased upon UV-light irradiation, accompanied by an increase in CD signals based on cis-azobenzene moieties. DFT calculations of the complexes indicated that intramolecular hydrogen bonds form between the amide moieties of two ligands in the cis-platinum complexes, resulting in retention of conformation. A noncovalent interaction plot analysis also indicated that the π–π interaction between the benzene rings of the ligands also contributes to conformational maintenance. The d-alanine-derived counterparts, D-2a-5t and D-2a-5c, exhibited mirror-image CD spectroscopic patterns in comparison to those of L-2a-5t and L-2a-5c. Solution-state IR absorption spectroscopic peaks of C═O stretching and N–H bending vibrations of L-2a-5c were observed broadly at ca. 10 cm–1 lower and higher than those of P(Ph)2-1,4-C6H4-CONH-C*H(CH3)-CONH-1,4-C6H4-N═N-Ph (L-2a), respectively, thus supporting the formation of intramolecular hydrogen bonding at the amide groups.

Symmetry, Combinatorics, Artificial Intelligence, Music and Spectroscopy

Symmetry forms the foundation of combinatorial theories and algorithms of enumeration such as Möbius inversion, Euler totient functions, and the celebrated Pólya’s theory of enumeration under the symmetric group action. As machine learning and artificial intelligence techniques play increasingly important roles in the machine perception of music to image processing that are central to many disciplines, combinatorics, graph theory, and symmetry act as powerful bridges to the developments of algorithms for such varied applications. In this review, we bring together the confluence of music theory and spectroscopy as two primary disciplines to outline several interconnections of combinatorial and symmetry techniques in the development of algorithms for machine generation of musical patterns of the east and west and a variety of spectroscopic signatures of molecules. Combinatorial techniques in conjunction with group theory can be harnessed to generate the musical scales, intensity patterns in ESR spectra, multiple quantum NMR spectra, nuclear spin statistics of both fermions and bosons, colorings of hyperplanes of hypercubes, enumeration of chiral isomers, and vibrational modes of complex systems including supergiant fullerenes, as exemplified by our work on the golden fullerene C150,000. Combinatorial techniques are shown to yield algorithms for the enumeration and construction of musical chords and scales called ragas in music theory, as we exemplify by the machine construction of ragas and machine perception of musical patterns. We also outline the applications of Hadamard matrices and magic squares in the development of algorithms for the generation of balanced-pitch chords. Machine perception of musical, spectroscopic, and symmetry patterns are considered.

Topological Characterization and Graph Entropies of Tessellations of Kekulene Structures: Existence of Isentropic Structures and Applications to Thermochemistry, Nuclear Magnetic Resonance, and Electron Spin Resonance.

Tessellations of kekulenes and cycloarenes are of considerable interest as nanomolecular belts in trapping and transportation of heavy metal ions and chloride ions, as they possess optimal electronic features and pore sizes. A class of cycloarenes called kekulenes have been the focus of several experimental and theoretical studies from the stand point of aromaticity, superaromaticity, chirality, and novel electrical and magnetic properties. In the present study, we investigate the entropies and topological characterization of different tessellations of kekulenes through topological computations of superaromatic structures with pores. We introduce the self-powered vertex degree-based topological indices and then derive the graph entropy measures for three different tessellations (zigzag, armchair, and rectangular) via various molecular descriptors that we derive here. Several applications to computing the molecular properties are pointed out. We demonstrate the existence of isentropic and yet nonisomorphic tessellations of kekulenes for the first time. The two tessellations are predicted to be quite close in energy with comparable energy gaps. Graph theory-based PPP methods with parameters derived from higher levels of theory are proposed to be promising tools for the predictions of relative stabilities of kekulene tessellations. We show that the developed techniques can be applied in the general context of artificial intelligence for the machine generation of nuclear magnetic resonance and electron spin resonance spectroscopic patterns as well as in robust computations of thermochemistry of a large combinatorial libraries of tessellations of kekulenes through the generation of bond-equivalence classes.

Synthesis, characterization, antimicrobial, cytotoxic, DNA-interaction, molecular docking and DFT studies of novel di- and tri-organotin(IV) carboxylates using 3-(3-nitrophenyl)2-methylpropenoic acid

One diorganotin(IV) [n-Bu2SnL2] (1) and two triorganotin(IV) carboxylates [n-Bu3SnL] (2) and [Ph3SnL] (3) [L = 3-(3-nitrophenyl) 2-methylpropenoic acid] were synthesized and characterized by elemental analysis, FT-IR and NMR (1H, 13C) spectroscopies. The geometry of complexes and binding mode of ligand were worked out through FT-IR and NMR spectroscopies. The ligand coordinate with Sn via carboxylato oxygen in monodentate fashion leading to four coordinated geometries around Sn center. The effectiveness of complexes towards their antimicrobial and cytotoxic potential was evaluated and a significant extent of antimicrobial potential was observed with a few exceptions. Molecular docking studies were performed for these complexes to check their interaction with DNA. Results from this study revealed that these compounds can bind favorably with cisplatin binding site and targeting the major groove of DNA. The complex-DNA interaction study was also performed through UV-Vis spectroscopic technique and viscosity measurement, and the observed experimental results were well matched with theoretical results. Computational vibrational analysis, frontier molecular orbital (FMO), natural bond orbitals (NBOs), linear and non-linear optical (NLO) properties of ligand and complexes 1-3 were calculated by density functional theory (DFT) and time-dependent DFT (TDDFT) using CAM-B3LYP/6-31G (d,p) level of theory to evaluate spectroscopic, structural parameters and reactivity patterns.

Thielavins: tuned biosynthesis and LR-HSQMBC for structure elucidation.

A series of thielavins I, V, and Q (1-3) and the previously undescribed thielavin Z8 (4) were isolated from cultures of a fungal Shiraia-like sp. (strain MSX60519) that were grown under a suite of media and light conditions, with enhanced biosynthesis noted using rice as a substrate with 12:12 h light:dark cycles. Conversely, oatmeal medium and continuous white LED light exposure negatively affected the production of these compounds, at least by strain MSX60519. The structure of 4 was determined using NMR spectroscopic data and mass fragmentation patterns. Of note, the utility of LR-HSQMBC and NOESY NMR experiments in the structural elucidation of these hydrogen-deficient natural products was demonstrated. Compounds 1-4 exhibited cytotoxic activity at the micromolar level against human breast, ovarian, and melanoma cancer cell lines.