CAST/CNMR: highly accurate 13C NMR chemical shift prediction system considering stereochemistry

Human- and computer-accessible 2D correlation data for a more reliable structure determination of organic compounds. Future roles of researchers, software developers, spectrometer managers, journal editors, reviewers, publisher and database managers toward artificial-intelligence analysis of NMR spectra

The introduction of a universal data format to report the correlation data of 2D NMR spectra such as COSY, HSQC and HMBC spectra will have a large impact on the reliability of structure determination of small organic molecules. These lists of assigned cross peaks will bridge signals found in NMR 1D and 2D spectra and the assigned chemical structure. The record could be very compact, human and computer readable so that it can be included in the supplementary material of publications and easily transferred into databases of scientific literature and chemical compounds. The records will allow authors, reviewers and future users to test the consistency and, in favorable situations, the uniqueness of the assignment of the correlation data to the associated chemical structures. Ideally, the data format of the correlation data should include direct links to the NMR spectra to make it possible to validate their reliability and allow direct comparison of spectra. In order to take the full benefits of their potential, the correlation data and the NMR spectra should therefore follow any manuscript in the review process and be stored in open-access database after publication. Keeping all NMR spectra, correlation data and assigned structures together at all time will allow the future development of validation tools increasing the reliability of past and future NMR data. This will facilitate the development of artificial intelligence analysis of NMR spectra by providing a source of data than can be used efficiently because they have been validated or can be validated by future users. Copyright © 2016 John Wiley & Sons, Ltd.

Total Synthesis of the Proposed Structure for Aromin and Its Structural Revision

This paper describes the first total synthesis of the proposed structure for aromin, an annonaceous acetogenin possessing an unusual bis-THF ring system, and its 4S,7R-isomer. The key steps involve an oxidative cyclization of a couple of terminal-diene alcohols and an intermolecular metathesis of an alkenyl tetrahydrofuran with an enone carrying a tetrahydrofuranyl lactone. The spectral data of both samples did not match those of aromin. Re-examination of the NMR data using the CAST/CNMR Structure Elucidator and chemical derivations suggested that the real structure of aromin should be revised to be a tetrahydropyran acetogenin, montanacin D. Cytotoxicities in human solid tumor cell lines for synthetic samples were also evaluated.

Fully automatic assignment of small molecules' NMR spectra without relying on chemical shift predictions

We present a method for the automatic assignment of small molecules' NMR spectra. The method includes an automatic and novel self-consistent peak-picking routine that validates NMR peaks in each spectrum against peaks in the same or other spectra that are due to the same resonances. The auto-assignment routine used is based on branch-and-bound optimization and relies predominantly on integration and correlation data; chemical shift information may be included when available to fasten the search and shorten the list of viable assignments, but in most cases tested, it is not required in order to find the correct assignment. This automatic assignment method is implemented as a web-based tool that runs without any user input other than the acquired spectra.

Synthesis and structural revision of a brominated sesquiterpenoid, aldingenin C

This paper describes a short step synthesis of the proposed structure for aldingenin C from trans-limonene oxide. The tetrahydropyran-fused 2-oxabicyclo[3.2.2]nonane skeleton as the structural feature was constructed by an intramolecular epoxide-opening reaction and a brominative cyclization. The spectral data of the synthetic compound did not match those of the natural product reported. Re-examination of the reported NMR data using new CAST/CNMR Structure Elucidator suggests that the structure of aldingenin C should be revised to that of known caespitol.

Chemical structure elucidation from ¹³C NMR chemical shifts: efficient data processing using bipartite matching and maximal clique algorithms

Computer-assisted chemical structure elucidation has been intensively studied since the first use of computers in chemistry in the 1960s. Most of the existing elucidators use a structure-spectrum database to obtain clues about the correct structure. Such a structure-spectrum database is expected to grow on a daily basis. Hence, the necessity to develop an efficient structure elucidation system that can adapt to the growth of a database has been also growing. Therefore, we have developed a new elucidator using practically efficient graph algorithms, including the convex bipartite matching, weighted bipartite matching, and Bron-Kerbosch maximal clique algorithms. The utilization of the two matching algorithms especially is a novel point of our elucidator. Because of these sophisticated algorithms, the elucidator exactly produces a correct structure if all of the fragments are included in the database. Even if not all of the fragments are in the database, the elucidator proposes relevant substructures that can help chemists to identify the actual chemical structures. The elucidator, called the CAST/CNMR Structure Elucidator, plays a complementary role to the CAST/CNMR Chemical Shift Predictor, and together these two functions can be used to analyze the structures of organic compounds.

Quantitative structure spectroscopy relationships of carbon-13 nuclear magnetic resonance chemical shifts of steroids

Quantitative structure spectroscopy relationships (QSSRs) are systematically studied for carbon-13 nuclear magnetic resonance ((13)C NMR) spectroscopic simulation of steroid compounds. Both the atomic electronegativity interaction vector (AEIV) and the atomic hybridization state index (AHSI) are used for the expression of local chemical microenvironment and atomic hybridization state of 4434 resonance carbon atoms in 203 steroid molecules. A multiple linear regression (MLR) model is built after screening some insignificant parameters with the stepwise multiple regression (SMR) technique. Correlation coefficients of the developed model are R(cum)(2)=0.9341 and Q(LOO)(2)=0.9336 for classical estimation of molecular modeling and the cross-validation with leave-one-out (LOO) procedures, respectively, primarily indicating that the MLR model has good modeling stability and prediction ability. Furthermore, the superior performance of the MLR model is tested by the leave-33%-out (L33%O) cross-validation method, where the mean correlation coefficients of three test sets are Q(2)=0.9310 and Q(ext)(2)=0.9196 for both internal and external sets. In conclusion, AEIV and AHSI descriptors can be used for estimating and predicting (13)C NMR chemical shifts of steroids.

Steroids: reactions and partial synthesis

This article reviews the progress in the chemistry of the steroids that was published between January and December 2003. The reactions and partial synthesis of estrogens, androgens, pregnanes, cholic acid derivatives, cholestanes and vitamin D analogues are covered. There are 152 references.