Simple method for identification of skeletons of aporphine alkaloids from 13C NMR data using artificial neural networks

This paper describes the use of artificial neural networks as a theoretical tool in the structural determination of alkaloids from (13)C NMR chemical shift data, aiming to identify skeletal types of those compounds. For that, 162 aporphine alkaloids belonging to 12 different skeletons were codified with their respective (13)C NMR chemical shifts. Each skeleton pertaining to aporphine alkaloid type was used as output, and the (13)C NMR chemical shifts were used as input data of the net. Analyzing the obtained results, one can then affirm the skeleton to which each one of these compounds belongs with high degree of confidence (over 97%). The relation between the correlation coefficient and the number of epochs and the architecture of net (3-layer MLP or 4-layer MLP) were analyzed, too. The analysis showed that the results predicted by the 3-layer MLP networks trained with a number of the epochs higher than 900 epochs are the best ones. The artificial neural nets were shown to be a simple and efficient tool to solve structural elucidation problems making use of (13)C NMR chemical shift data, even when a similarity between the searched skeletons occurs, offering fast and accurate results to identification of skeletons of organic compounds.     

Automated structure elucidation of organic molecules from (13)c NMR spectra using genetic algorithms and neural networks.

The automated structure elucidation of organic molecules from experimentally obtained properties is extended by an entirely new approach. A genetic algorithm is implemented that uses molecular constitution structures as individuals. With this approach, the structure of organic molecules can be optimized to meet experimental criteria, if in addition a fast and accurate method for the prediction of the used physical or chemical features is available. This is demonstrated using (13)C NMR spectrum as readily obtainable information. (13)C NMR chemical shift, intensity, and multiplicity information is available from (13)C NMR DEPT spectra. By means of artificial neural networks a fast and accurate method for calculating the (13)C NMR spectrum of the generated structures exists. The approach is limited by the size of the constitutional space that has to be searched and by the accuracy of the shift prediction for the unknown substance. The method is implemented and tested successfully for organic molecules with up to 20 non-hydrogen atoms.     

Application of Artificial Neural Networks for Analysis of 13C NMR Spectra of Fucoidans

A new approach for structure determination of native and O-desulfated fucoidans by the analysis of their ¹³C NMR spectra by artificial neural networks (ANNs) is described. Two ANN models were studied: the simple three-layer feed-forward network, which employs supervised learning, and the adaptive resonance theory (ART) network with unsupervised learning. Training sets for the networks were constructed using chemical shifts of synthetic oligofucosides. The results obtained demonstrate that both models worked better in the case of desulfated fucoidans, while the ART-type networks gave better results in sulfated (native) fucoidan structure elucidation.     

Genius: a genetic algorithm for automated structure elucidation from 13C NMR spectra

The automated structure elucidation of organic molecules from experimentally obtained properties is extended by an entirely new approach. A genetic algorithm is implemented that uses molecular constitution structures as individuals. With this approach, the structure of organic molecules can be optimized to meet experimental criteria, if in addition a fast and accurate method for the prediction of the used physical or chemical features is available. This is demonstrated using 13C NMR spectrum as readily obtainable information. By means of artificial neural networks a fast and accurate method for calculating the 13C NMR spectrum of the generated structures exists. The method is implemented and tested successfully for organic molecules with up to 18 non-hydrogen atoms.     

Automatic assignment of absolute configuration from 1D NMR data

[reaction: see text] Opposite enantiomers exhibit different NMR properties in the presence of an external common chiral element, and a chiral molecule exhibits different NMR properties in the presence of external enantiomeric chiral elements. Automatic prediction of such differences, and comparison with experimental values, leads to the assignment of the absolute configuration. Here two cases are reported, one using a dataset of 80 chiral secondary alcohols esterified with (R)-MTPA and the corresponding (1)H NMR chemical shifts and the other with 94 (13)C NMR chemical shifts of chiral secondary alcohols in two enantiomeric chiral solvents. For the first application, counterpropagation neural networks were trained to predict the sign of the difference between chemical shifts of opposite stereoisomers. The neural networks were trained to process the chirality code of the alcohol as the input, and to give the NMR property as the output. In the second application, similar neural networks were employed, but the property to predict was the difference of chemical shifts in the two enantiomeric solvents. For independent test sets of 20 objects, 100% correct predictions were obtained in both applications concerning the sign of the chemical shifts differences. Additionally, with the second dataset, the difference of chemical shifts in the two enantiomeric solvents was quantitatively predicted, yielding r(2) 0.936 for the test set between the predicted and experimental values.     

Comparative structural connectivity spectra analysis (CoSCoSA) models of steroid binding to the corticosteroid binding globulin

A three-dimensional quantitative spectrometric data-activity relationship (3D-QSDAR) model was developed that is built by combining NMR spectral information with structural information in a 3D-connectivity matrix. The 3D-connectivity matrix is built by displaying all possible carbon-to-carbon connections with their assigned carbon NMR chemical shifts and distances between the carbons. Selected 2D (13)C-(13)C COrrelation SpectroscopY (COSY) (through-bond nearest neighbors) and selected theoretical 2D (13)C-(13)C distance connectivity spectral slices from the 3D-connectivity matrix to produce a relationship among the spectral patterns for 30 steroids binding to corticosteroid binding globulin. We call this technique a comparative structural connectivity spectra analysis (CoSCoSA) modeling. A CoSCoSA principal component linear regression model based on the combination of (13)C-(13)C COSY and (13)C-(13)C distance spectra principal components (PCs) had an r(2) of 0.96 and a leave-one-out (LOO) cross-validation q(2) of 0.92. A CoSCoSA parallel distributed artificial neural network (PD-ANN) model based on the combination of (13)C-(13)C COSY and (13)C-(13)C distance spectra had an r(2) of 0.96, a leave-three-out q(3)(2) of 0.78, and a leave-ten-out q(10)(2) of 0.73. CoSCoSA modeling attempts to uniquely combine the quantum mechanics information from the NMR chemical shifts with internal molecular atom-to-atom distances into an accurate modeling technique. The CoSCoSA modeling technique has the flexibility and accuracy to outperform the cross-validated variance q(2) of previously published quantitative structure-activity relationship (QSAR), quantitative spectral data-activity relationship (QSDAR), self-organizing map (SOM), and electrotopological state (E-state) models.     

Carbon-13 NMR spectra of monosubstituted pyrazines

Carbon-13 NMR chemical shifts and one-bond carbon–hydrogen coupling constants have been obtained at 15·09 MHz. The trends in the carbon chemical shifts obtained for the pyrazines parallel those of monosubstituted benzenes and 2-substituted pyridines, except for the direct effect of substitution where the pyrazines resemble pyridines not benzenes. The substituent effects on the ¹³C NMR spectra are generally quite similar to those in the ¹H NMR spectra. The ¹³C NMR spectrum of the tautomeric hydroxypyrazine has been compared with the ¹³C NMR spectra of 2-, 3- and 4-hydroxypyridines. Hydroxy compounds that can exist as a cyclic amide show a large meta substituent effect on the chemical carbon shift.     

Structural analysis of alanine tripeptide with antiparallel and parallel beta-sheet structures in relation to the analysis of mixed beta-sheet structures in Samia cynthia ricini silk protein fiber using solid-state NMR spectroscopy

The structural analysis of natural protein fibers with mixed parallel and antiparallel beta-sheet structures by solid-state NMR is reported. To obtain NMR parameters that can characterize these beta-sheet structures, (13)C solid-state NMR experiments were performed on two alanine tripeptide samples: one with 100% parallel beta-sheet structure and the other with 100% antiparallel beta-sheet structure. All (13)C resonances of the tripeptides could be assigned by a comparison of the methyl (13)C resonances of Ala(3) with different [3-(13)C]Ala labeling schemes and also by a series of RFDR (radio frequency driven recoupling) spectra observed by changing mixing times. Two (13)C resonances observed for each Ala residue could be assigned to two nonequivalent molecules per unit cell. Differences in the (13)C chemical shifts and (13)C spin-lattice relaxation times (T(1)) were observed between the two beta-sheet structures. Especially, about 3 times longer T(1) values were obtained for parallel beta-sheet structure as compared to those of antiparallel beta-sheet structure, which could be explicable by the difference in the hydrogen-bond networks of both structures. This very large difference in T(1) becomes a good measure to differentiate between parallel or antiparallel beta-sheet structures. These differences in the NMR parameters found for the tripeptides may be applied to assign the parallel and antiparallel beta-sheet (13)C resonances in the asymmetric and broad methyl spectra of [3-(13)C]Ala silk protein fiber of a wild silkworm, Samia cynthia ricini.     

Automatic identification of terpenoid skeletons by feed-forward neural networks

Feed-forward neural networks (FFNNs) were used to predict the skeletal type of molecules belonging to six classes of terpenoids. A database that contains the ¹³C NMR spectra of about 5000 compounds was used to train the FFNNs. An efficient representation of the spectra was designed and the constitution of the best FFNN input vector format resorted from an heuristic approach. The latter was derived from general considerations on terpenoid structures.     

Heterocyclization of electrophilic alkenes with tetranitromethane revisited: regiochemistry and the mechanism of nitroisoxazole formation

Revised regiochemistry for the heterocyclization of electrophilic alkenes with tetranitromethane (TNM) in the presence of triethylamine, providing rapid access to nitroisoxazoles, is reported. The formation of 5-nitroisoxazoles previously incorrectly assigned as 3-nitro regioisomers, has now been established unambiguously by X-ray crystallography. Empirical computations with ACD/CNMR Predictor, based both on hierarchical ordering of spherical environments (HOSE) and an algorithm of artificial neural networks (ANN), and also Density Functional Theory computations of the ¹³C NMR chemical shifts for the 3- versus 5-nitroisoxazoles are shown to consistently match the spectra of the experimentally observed 5-regioisomers.     

氧氟沙星的核磁共振波谱性质研究

结合1H, 13C NMR, DEPT, COSY, HSQC, HMBC谱和碳氟偶合裂分行为, 对酸性及碱性溶液中氧氟沙星(Ofloxacin, OFL)的1H和13C谱分别进行归属, 研究了哌嗪环亚甲基构成的AA'BB'复杂自旋体系中各H的化学位移. 发现噁嗪环上的甲基处于直立键; 5H在酸性溶液中化学位移移向低场, 这可能与形成C—H…O弱氢键有关; 在碱性溶液中, OFL的羧基变为羧酸根, 造成羧基和羰基周围碳原子上π电子重新分布, 导致相应C的化学位移和碳氟偶合常数发生明显变化.     

Electronic structure and solvatochromism of merocyanines NMR spectroscopic point of view

(1)H and (13)C NMR spectra of two series of malononitrile-based merocyanines, which possess positive and negative solvatochromism have been in detail investigated in low polar chloroform and polar dimethyl sulfoxide (DMSO). Careful attribution of signals in spectra has been made with the help of two-dimensional NMR experiments (COSY, NOESY, HMBC, and HMQC). Hence, the dependence of merocyanines electronic structure on their chemical structure and solvent nature has been studied by this powerful method. It has been shown that there exists a good correlation between the calculated charges on carbon atoms of a polymethine chain and their chemical shifts in (13)C NMR spectra. The influence of solvent polarity on bond orders for dyes with positive and negative solvatochromism is also observed. The comparison of (13)C NMR spectra of merocyanines and corresponding parent ionic dyes allows to determine their sign of solvatochromism irrespectively of electronic spectra, and also to find the key atoms of chromophore whose signals in (13)C NMR spectra are most informative.     

An application of neural networks in chemistry. Prediction of13C NMR chemical shifts

Basic definitions of neural networks are given in terms of oriented graphs. Partial derivatives of an objective function with respect to the weight and threshold coefficients are derived. These derivatives are very important for the adaptation process, carried out by a version of the gradient method of We neural network considered. The stability of the adapted neural network toward small changes — perturbation — of input activities is described by sensitivities. The theory is illustrated by application of simple neural networks that reflect the topology of molecules to the classification of¹³C NMR chemical shifts of secondary carbons in acyclic alkanes.     

G-matrix Fourier transform NOESY-based protocol for high-quality protein structure determination

A protocol for high-quality structure determination based on G-matrix Fourier transform (GFT) NMR is presented. Five through-bond chemical shift correlation experiments providing 4D and 5D spectral information at high digital resolution are performed for resonance assignment. These are combined with a newly implemented (4,3)D GFT NOESY experiment which encodes information of 4D 15N/15N-, 13C(alipahtic)/15N-, and 13C(aliphatic)/13C(aliphatic)-resolved [1H,1H]-NOESY in two subspectra, each containing one component of chemical shift doublets arising from 4D --> 3D projection at omega1:Omega(1H) +/- Omega(X) [X = 15N,13C(aliphatic)]. The peaks located at the centers of the doublets are obtained from simultaneous 3D 15N/13C(aliphatic)/13C(aromatic)-resolved [1H,1H]-NOESY, wherein NOEs detected on aromatic protons are also obtained. The protocol was applied for determining a high-quality structure of the 14 kDa Northeast Structural Genomics consortium target protein, YqfB (PDB ID ). Through-bond correlation and NOESY spectra were acquired, respectively, in 16.9 and 39 h (30 h for shift doublets, 9 h for central peaks) on a 600 MHz spectrometer equipped with a cryogenic probe. The rapidly collected highly resolved 4D NOESY information allows one to assign the majority of NOEs directly from chemical shifts, which yields accurate initial structures "within" approximately 2 angstroms of the final structure. Information theoretical "QUEEN" analysis of initial distance limit constraint networks revealed that, in contrast to structure-based protocols, such NOE assignment is not biased toward identifying additional constraints that tend to be redundant with respect to the available constraint network. The protocol enables rapid NMR data collection for robust high-quality structure determination of proteins up to approximately 20-25 kDa in high-throughput.     

测试温度对聚苯基缩水甘油醚的~(13)C-核磁共振谱的影响

^13C核磁共振谱（^13C－NMR）的化学位移对碳核所处的化学环境十分敏感,因此它是表征聚合物立构规整度的有效手段,常规^13C-NMR谱为质子噪声去偶谱,因各种碳核驰豫速率不同,谱线强度与碳原子数不成正比,为了使谱线强度与碳原子数成正比,以达到定量分析的目的,加大脉冲间隔是一种有效的方法。     

α-aminoazoles in synthesis of heterocycles: III. 4-trifluoromethylpyrazolo[3,4-<Emphasis Type="Italic">b</Emphasis>]pyridines: Synthesis and structure

Cyclocondensation of N-substituted 5-aminopyrazoles with fluorinated 1,3-diketones yielded 4-trifluoromethyl-substituted pyrazolo[3,4-b]pyridines as the only reaction products. The regiostructure of compounds obtained was proved by ¹H and ¹³C NMR homo- and heteronuclear correlation spectroscopy. Characteristic chemical shifts in the ¹³C NMR spectra of regioisomeric pyrazolo[3,4-b]pyridines were established.     

Butene concentration prediction in ethylene/propylene/1-butene terpolymers by FT-IR spectroscopy through multivariate statistical analysis and artificial neural networks

This paper reports the development of calibration models for quality control in the production of ethylene/propylene/1-butene terpolymers by the use of multivariate tools and FT-IR spectroscopy.1-Butene concentration prediction is achieved in terpolymers by coupling FT-IR spectroscopy to multivariate regression tools. A dataset of 26 terpolymers (14 coming from a constrained experimental design for mixtures, plus 12 terpolymers used for external validation) was analysed by FT-IR spectroscopy. An internal method of “Polimeri Europa” plant, based on ¹³C NMR spectroscopy is used to determine the percentage of 1-butene in the samples. Then, different multivariate tools are used for 1-butene concentration prediction based on the FT-IR spectra recorded. Different multivariate calibration methods were explored: principal component regression (PCR), partial least squares (PLS), stepwise OLS regression (SWR) and artificial neural networks (ANNs). The model obtained by back-propagation neural networks turned out to be the best one. The performances of the BP-ANN model were further improved by variable selection procedures based on the calculation of the first derivative of the network.The proposed approach allows the monitoring in real time of the polymer synthesis and the estimation of the characteristics of the product attainable from the concentration of 1-butene.     

Complete Solid State 13C NMR Chemical Shift Assignments for α-D-Glucose, α-D-Glucose-H2O and β-D-Glucose

Abstract

NMR spectra of crystalline α-D-glucose DH₂O (1), α-D-glucose (2), and β-D-glucose (3) were examined by 13C cross polarization magic angle spinning (CPMAS) methods. Each of the three forms of glucose exhibited a distinctly different spectrum. Chemical interconversion of 2 and 3 as well as the in situ dehydration of 1 during the course of the CPMAS NMR experiment was monitored in the ¹³C spectra. Samples of 1, 2, and 3 specifically enriched at C-1 and C-6 with ¹³C yielded ¹³C spectra in which the resonances corresponding to the adjacent C-2 and C-5 carbons were not visible due to strong homonuclear ¹³C dipolar interactions with the high abundance label. Spectra of these analogues as well as the C-2 and C-3 labeled materials provided the complete ¹³C chemical shift assignments of crystalline 1 2, and 3. A comparison of the solid state and solution ¹³C spectra revealed substantial resonance shifts for each of the three structures examined.