Automatic structure determination of organic molecules: Principle and implementation of the LSD program

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.

Automatic Structure Elucidation through Data Base Search and 2D NMR Spectral Analysis

This work shows how two expert systems, LSD and SISTEMAT, can be used together to solve structure elucidation problems that were selected from recent literature articles. The LSD system is a structure generator that mainly relies on homo- and heteronuclear 2D NMR data. It lacks the knowledge of chemical shift values and of natural product chemistry. Conversely, the SISTEMAT data base contains about 20000 natural compounds and refers to both their 13C NMR chemical shifts and their botanical origin. When exploited by dedicated computer programs it yields structural constraints such as skeletal types and ring systems. The botanical and spectroscopic data in SISTEMAT proved to be very complementary in the constraints extraction process. Several application examples of the proposed methodology are described in detail.

Tutorial for the structure elucidation of small molecules by means of the LSD software

Automatic structure elucidation of small molecules by means of the "logic for structure elucidation" (LSD) software is introduced in the context of the automatic exploitation of chemical shift correlation data and with minimal input from chemical shift values. The first step in solving a structural problem by means of LSD is the extraction of pertinent data from the 1D and 2D spectra. This operation requires the labeling of the resonances and of their correlations; its reliability highly depends on the quality of the spectra. The combination of COSY, HSQC, and HMBC spectra results in proximity relationships between nonhydrogen atoms that are associated in order to build the possible solutions of a problem. A simple molecule, camphor, serves as an example for the writing of an LSD input file and to show how solution structures are obtained. An input file for LSD must contain a nonambiguous description of each atom, or atom status, which includes the chemical element symbol, the hybridization state, the number of bound hydrogen atoms and the formal electric charge. In case of atom status ambiguity, the pyLSD program performs clarification by systematically generating the status of the atoms. PyLSD also proposes the use of the nmrshiftdb algorithm in order to rank the solutions of a problem according to the quality of the fit between the experimental carbon-13 chemical shifts, and the ones predicted from the proposed structures. To conclude, some hints toward future uses and developments of computer-assisted structure elucidation by LSD are proposed.

The octet rule in chemical space: generating virtual molecules

We present a generator of virtual molecules that selects valid chemistry on the basis of the octet rule. Also, we introduce a mesomer group key that allows a fast detection of duplicates in the generated structures. Compared to existing approaches, our model is simpler and faster, generates new chemistry and avoids invalid chemistry. Its versatility is illustrated by the correct generation of molecules containing third-row elements and a surprisingly adept handling of complex boron chemistry. Without any empirical parameters, our model is designed to be valid also in unexplored regions of chemical space. One first unexpected finding is the high prevalence of dipolar structures among generated molecules.

Computer-aided Dereplication and Structure Elucidation of Natural Products at the University of Reims

Natural product chemistry began in Reims, France, in a pharmacognosy research laboratory whose main emphasis was the isolation and identification of bioactive molecules, following the guidelines of chemotaxonomy. The structure elucidation of new compounds of steadily increasing complexity favored the emergence of methodological work in nuclear magnetic resonance. As a result, our group was the first to report the use of proton-detected heteronuclear chemical shift correlation spectra for the computer-assisted structure elucidation of small organic molecules driven by atom proximity relationships and without relying on databases. The early detection of known compounds appeared as a necessity in order to deal more efficiently with complex plant extracts. This goal was reached by an original combination of mixture fractionation by centrifugal partition chromatography, analysis by ¹³ C NMR, digital data reduction and alignment, hierarchical data clustering, and computer database search.

Novel triterpenoid derivatives from Eucomis bicolor Bak. (Hyacinthaceae: Hyacinthoideae)

The bulbs of Eucomis bicolor (Hyacinthoideae) yielded fourteen novel compounds, including (17S)-3-oxo-24,25,26,27,28-pentanorlanost-8-en-23,17α-olide, whose structure was determined using the Logic for Structure Determination Program.

Exploiting the Complementarity between Dereplication and Computer-Assisted Structure Elucidation for the Chemical Profiling of Natural Cosmetic Ingredients: Tephrosia purpurea as a Case Study

The aqueous-ethanolic extract of Tephrosia purpurea seeds is currently exploited in the cosmetic industry as a natural ingredient of skin lotions. The aim of this study was to chemically characterize this ingredient by combining centrifugal partition extraction (CPE) as a fractionation tool with two complementary identification approaches involving dereplication and computer-assisted structure elucidation. Following two rapid fractionations of the crude extract (2 g), seven major compounds namely, caffeic acid, quercetin-3-O-rutinoside, ethyl galactoside, ciceritol, stachyose, saccharose, and citric acid, were unambiguously identified within the CPE-generated simplified mixtures by a recently developed (13)C NMR-based dereplication method. The structures of four additional compounds, patuletin-3-O-rutinoside, kaempferol-3-O-rutinoside, guaiacylglycerol 8-vanillic acid ether, and 2-methyl-2-glucopyranosyloxypropanoic acid, were automatically elucidated by using the Logic for Structure Determination program based on the interpretation of 2D NMR (HSQC, HMBC, and COSY) connectivity data. As more than 80% of the crude extract mass was characterized without need for tedious and labor-intensive multistep purification procedures, the identification tools involved in this work constitute a promising strategy for an efficient and time-saving chemical profiling of natural extracts.

Recent advances in the structure elucidation of small organic molecules by the LSD software

The LSD software proposes the structures of small organic molecules that fit with structural constraints from 1D and 2D NMR spectroscopy. Its initial design introduced limits that needed to be eliminated to extend its scope and help its users choose the most likely structure among those proposed. The LSD software code has been improved, so that it recognizes a wider set of atom types to build molecules. More flexibility has been given in the interpretation of 2D NMR data, including the automatic detection of very long-range correlations. A program named pyLSD was written to deal with problems in which atom types are ambiguously defined. It also provides a (13)C NMR chemical shift-based solution ranking algorithm. PyLSD was able to propose the correct structure of hexacyclinol, a natural product whose structure determination has been highly controversal. The solution was ranked first within a list of ten structures that were produced by pyLSD from the literature NMR data. The structure of an aporphin natural product was determined by pyLSD, taking advantage of the possibility of handling electrically charged atoms. The structure generation of the insect antifeedant azadirachtin by LSD was reinvestigated by pyLSD, considering that three (13)C resonances did not lead to univocal hybridization states.

Structure verification through computer-assisted spectral assignment of NMR spectra

The validation of a molecular organic structure on the basis of 1D and 2D HSQC, COSY and HMBC NMR spectra is proposed as an alternative to the methods that are mainly based on chemical shift prediction. The CCASA software was written for this purpose. It provides an updated and improved implementation of the preceding computer-assisted spectral assignment software. CCASA can be downloaded freely from http://www.univ-reims.fr/LSD/JmnSoft/CASA. Two bioactive natural products, a triterpene and a benzophenone, were selected from literature data as examples. The tentative matching between the structure and the NMR data interpretation of the triterpene unexpectedly leads to the hypothesis of an incorrect structure. The LSD software was used to find an alternative structure that improved the 2D NMR data interpretation and the carbon-13 chemical shift matching between experimental values and those produced by the nmrshiftdb2 prediction tool. The benzophenone example showed that signal assignment by means of chemical shift prediction can be replaced by elementary user-supplied chemical shift and multiplicity constraints.

Cembranolides from the stem bark of the southern African medicinal plant, Croton gratissimus (Euphorbiaceae)

The stem bark of Croton gratissimus (Euphorbiaceae) yielded four cembranolides, including the first reported example of a 2,12-cyclocembranolide, (+)-[1R*,2S*,7S*,8S*,12R*]-7,8-epoxy-2,12-cyclocembra-3E,10Z-dien-20,10-olide, whose structure was confirmed by means of single crystal X-ray analysis. This compound showed moderate activity against the PEO1 and PEO1TaxR ovarian cancer cell lines.

New Improvements in Automatic Structure Elucidation Using the LSD (Logic for Structure Determination) and the SISTEMAT Expert Systems

This article describes the integration of the LSD (Logic for Structure Determination) and SISTEMAT expert systems that were both designed for the computer-assisted structure elucidation of small organic molecules. A first step has been achieved towards the linking of the SISTEMAT database with the LSD structure generator. The skeletal descriptions found by the SISTEMAT programs are now easily transferred to LSD as substructural constraints. Examples of the synergy between these expert systems are given for recently reported natural products.

A systematic approach for the generation and verification of structural hypotheses

During the process of molecular structure elucidation the selection of the most probable structural hypothesis may be based on chemical shift prediction. The prediction is carried out using either empirical or quantum-mechanical (QM) methods. When QM methods are used, NMR prediction commonly utilizes the GIAO option of the DFT approximation. In this approach the structural hypotheses are expected to be investigated by scientist. In this article we hope to show that the most rational manner by which to create structural hypotheses is actually by the application of an expert system capable of deducing all potential structures consistent with the experimental spectral data and specifically using 2D NMR data. When an expert system is used the best structure(s) can be distinguished using chemical shift prediction, which is best performed either by an incremental or neural net algorithm. The time-consuming QM calculations can then be applied, if necessary, to one or more of the 'best' structures to confirm the suggested solution.

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.

The structural elucidation of a novel iridoid derivative from Tachiadenus longiflorus (Gentianaceae) using the LSD programme and quantum chemical computations

Oleanolic acid, scoparone, scopoletin and a novel iridoid derivative, angelone, were isolated from Tachiadenus longiflorus (Gentianaceae). The structure of angelone was determined from NMR data, given as input to the Logic for Structure Determination Programme, and was finally confirmed by comparison of experimental 13C-NMR chemical shifts with those obtained by quantum mechanical calculations.