CASE-DFT Structure Elucidation of Proton-Deficient Chlorodepsidones from the Indonesian Lichen and Structure Revision of Flavicansone.

Biodiscovery efforts in Indonesia have aimed to explore the understudied chemical diversity of its rich lichen flora, seeking to find new products endowed with significant biological properties. The chemical screening of a extract led to selection of this species for further investigation. LC/MS and H NMR-based dereplication pinpointed six chlorodepsidones from the thallus of a sample of this lichen.

Ominoxanthone-The First Xanthone Linearly Fused to a γ-Lactone from Bidaud Basidiomata. CASE- and DFT-Based Structure Elucidation.

The UHPLC-HRMS analysis of basidiomata extract revealed that this mushroom accumulated elevated yields of an unreported specialized metabolite. The molecular formula of this unknown compound, CHO, indicated that a challenging structure elucidation lay ahead, owing to its critically low H/C atom ratio. The structure of this new isolate, namely ominoxanthone (), could not be solved from the interpretation of the usual set of 1D/2D NMR data that conveyed too limited information to afford a single, unambiguous structure.

Enhancing computer-assisted structure elucidation with DFT analysis of J-couplings.

Computer-assisted structure elucidation (CASE) is the class of expert systems that derives molecular structures primarily from one-dimensional and two-dimensional nuclear magnetic resonance data. Contemporary CASE systems, including Advanced Chemistry Development/Structure Elucidator (ACD/SE), consider cross-peaks in heteronuclear multiple bond coherence (HMBC) and correlation spectroscopy (COSY) spectra as two- or three-bond correlations by default. However, four and more bond correlations (nonstandard correlations [NSCs]) could be present in these spectra too.

Towards unbiased and more versatile NMR-based structure elucidation: A powerful combination of CASE algorithms and DFT calculations.

Computer-assisted structure elucidation (CASE) is composed of two steps: (a) generation of all possible structural isomers for a given molecular formula and 2D NMR data (COSY, HSQC, and HMBC) and (b) selection of the correct isomer based on empirical chemical shift predictions. This method has been very successful in solving structural problems of small organic molecules and natural products. However, CASE applications are generally limited to structural isomer problems and can sometimes be inconclusive due to insufficient accuracy of empirical shift predictions.

Synergistic Combination of CASE Algorithms and DFT Chemical Shift Predictions: A Powerful Approach for Structure Elucidation, Verification, and Revision.

Structure elucidation of complex natural products and new organic compounds remains a challenging problem. To support this endeavor, CASE (computer-assisted structure elucidation) expert systems were developed. These systems are capable of generating a set of all possible structures consistent with an ensemble of 2D NMR data followed by selection of the most probable structure on the basis of empirical NMR chemical shift prediction.

Blind trials of computer-assisted structure elucidation software.

Background: One of the largest challenges in chemistry today remains that of efficiently mining through vast amounts of data in order to elucidate the chemical structure for an unknown compound. The elucidated candidate compound must be fully consistent with the data and any other competing candidates efficiently eliminated without doubt by using additional data if necessary. It has become increasingly necessary to incorporate an in silico structure generation and verification tool to facilitate this elucidation process.

Enhanced automated structure elucidation by inclusion of two-bond specific data.

The availability of cryogenically cooled probes permits routine acquisition of data from low sensitivity pulse sequences such as inadequate and 1,1-adequate. We demonstrate that the use of cryo-probe generated 1,1-adequate data in conjunction with HMBC dramatically improves computer-assisted structure elucidation (CASE) both in terms of speed and accuracy of structure generation. In this study data were obtained on two dissimilar natural products and subjected to CASE analysis with and without the incorporation of two-bond specific data.

The application of empirical methods of (13)C NMR chemical shift prediction as a filter for determining possible relative stereochemistry.

The reliable determination of stereocenters contained within chemical structures usually requires utilization of NMR data, chemical derivatization, molecular modeling, quantum-mechanical (QM) calculations and, if available, X-ray analysis. In this article, we show that the number of stereoisomers which need to be thoroughly verified, can be significantly reduced by the application of NMR chemical shift calculation to the full stereoisomer set of possibilities using a fragmental approach based on HOSE codes. The applicability of this suggested method is illustrated using experimental data published for a series of complex chemical structures.

Toward more reliable 13C and 1H chemical shift prediction: a systematic comparison of neural-network and least-squares regression based approaches.

The efficacy of neural network (NN) and partial least-squares (PLS) methods is compared for the prediction of NMR chemical shifts for both 1H and 13C nuclei using very large databases containing millions of chemical shifts. The chemical structure description scheme used in this work is based on individual atoms rather than functional groups. The performances of each of the methods were optimized in a systematic manner described in this work.

Fuzzy structure generation: a new efficient tool for Computer-Aided Structure Elucidation (CASE).

Contemporary Computer-Aided Structure Elucidation (CASE) systems are heavily based on the utilization of 2D NMR spectra. The utilization of HMBC/GHMBC and COSY/GCOSY correlations generally assumes that these correlations result from (2-3)JCH and (2-3)JHH spin-spin couplings, respectively, and consequently these values are used as the default setting in these systems. Our previous studies1,2 have shown that about half of the problems studied actually contain some correlations of 4-6 bonds, so-called "nonstandard" correlations.

Are deterministic expert systems for computer-assisted structure elucidation obsolete?

Expert systems for spectroscopic molecular structure elucidation have been developed since the mid-1960s. Algorithms associated with the structure generation process within these systems are deterministic; that is, they are based on graph theory and combinatorial analysis. A series of expert systems utilizing 2D NMR spectra have been described in the literature and are capable of determining the molecular structures of large organic molecules including complex natural products.

Structure elucidation from 2D NMR spectra using the StrucEluc expert system: detection and removal of contradictions in the data.

The elucidation of chemical structures from 2D NMR data commonly utilizes a combination of COSY, HMQC/HSQC, and HMBC data. Generally COSY connectivities are assumed to mostly describe the separation of protons that are separated by 1 skeletal bond (3JHH), while HMBC connectivities represent protons separated from carbon atoms by 1 to 2 skeletal bonds (2JCH and 3JCH). Obviously COSY and HMBC connectivities of lengths greater than those described have been detected.

Structure Elucidator: a versatile expert system for molecular structure elucidation from 1D and 2D NMR data and molecular fragments.

StrucEluc is an expert system that allows the computer-assisted elucidation of chemical structures based on the inputs of a series of spectral data including 1D and 2D NMR and mass spectra. The system has been enabled to allow a chemist to utilize fragments stored in a fragment database as well as user-defined fragments submitted by the chemist in the structure elucidation process. The association of fragments in this way has been shown to dramatically speed up the process of structure generation from 2D NMR data and has helped to minimize or eliminate the need for user intervention thereby further enabling the vision of automated elucidation.

Application of a new expert system for the structure elucidation of natural products from their 1D and 2D NMR data.

Described herein are applications of the latest version of the StrucEluc expert software system, enhanced to use 2D NMR data, to the structure elucidation of 60 recently isolated natural products. In this study, selected molecules containing between 15 and 65 skeletal atoms and having molecular masses ranging from 200 to 900 amu have been investigated. The correct structure was determined unambiguously for 58 of these molecules.