[show abstract][hide abstract] ABSTRACT: The elucidated structure of asperjinone (1), a natural product isolated from thermophilic Aspergillus terreus, was revised using the expert system Structure Elucidator. The reliability of the revised structure (2) was confirmed using 180 structures containing the (3,3-dimethyloxiran-2-yl)methyl fragment (3) as a basis for comparison and whose chemical shifts contradict the suggested structure (1).
Journal of Natural Products 01/2013; · 3.29 Impact Factor
[show abstract][hide abstract] ABSTRACT: General principles of the construction of expert systems for the elucidation of the structure of molecules from their spectra
were considered. The principal attention was focused on systems based on the use of 2-D NMR spectra. The structural information
extracted from 2D NMR spectra was characterized, and the strategy was outlined for structure elucidation under the conditions
when the analyzed spectrostructural information is incomplete, fuzzy, and contradictory. The most advanced expert system ACD/Structure
Elucidator, which is capable of determining the structure and stereochemistry of large molecules, in particular, those typical
in the chemistry of natural compounds, is described as an example.
Journal of Analytical Chemistry 04/2012; 63(1):13-20. · 0.62 Impact Factor
[show abstract][hide abstract] ABSTRACT: Structure elucidation using 2D NMR data and application of traditional methods of structure elucidation are known to fail for certain problems. In this work, it is shown that computer-assisted structure elucidation methods are capable of solving such problems. We conclude that it is now impossible to evaluate the capabilities of novel NMR experimental techniques in isolation from expert systems developed for processing fuzzy, incomplete and contradictory information obtained from 2D NMR spectra.
Magnetic Resonance in Chemistry 01/2012; 50(1):22-7. · 1.53 Impact Factor
[show abstract][hide abstract] ABSTRACT: 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. Dramatic improvements in both structure calculation times and structure candidates were observed by the inclusion of the two-bond specific data.
Magnetic Resonance in Chemistry 08/2010; 48(8):571-4. · 1.53 Impact Factor
[show abstract][hide abstract] ABSTRACT: Identification of degradants of pharmaceuticals is a necessary challenge of the drug development process following the subjection of candidate molecules to a variety of physico-chemical stresses. It would be desirable to be able to conduct such studies on a minimal amount of material. As a prototypical study, the isolation and identification of degradants of a sample of the complex indoloquinoline alkaloid, cryptospirolepine, was undertaken after prolonged storage in DMSO solution using a combination of cryogenic NMR probe technology and CASE (Computer-Assisted Structure Elucidation) programs. None of the starting alkaloid remained after storage; a chromatogram of the DMSO solution demonstrated the presence of >25 components in the mixture. The two most abundant degradation products were identified as the known alkaloid cryptolepinone (∼35%) and an unprecedented rearrangement product, DP-2, (∼16%).
[show abstract][hide abstract] ABSTRACT: This article coincides with the 40 year anniversary of the first published works devoted to the creation of algorithms for computer-aided structure elucidation (CASE). The general principles on which CASE methods are based will be reviewed and the present state of the art in this field will be described using, as an example, the expert system Structure Elucidator.
The developers of CASE systems have been forced to overcome many obstacles hindering the development of a software application capable of drastically reducing the time and effort required to determine the structures of newly isolated organic compounds. Large complex molecules of up to 100 or more skeletal atoms with topological peculiarity can be quickly identified using the expert system Structure Elucidator based on spectral data. Logical analysis of 2D NMR data frequently allows for the detection of the presence of COSY and HMBC correlations of "nonstandard" length. Fuzzy structure generation provides a possibility to obtain the correct solution even in those cases when an unknown number of nonstandard correlations of unknown length are present in the spectra. The relative stereochemistry of big rigid molecules containing many stereocenters can be determined using the StrucEluc system and NOESY/ROESY 2D NMR data for this purpose.
The StrucEluc system continues to be developed in order to expand the general applicability, provide improved workflows, usability of the system and increased reliability of the results. It is expected that expert systems similar to that described in this paper will receive increasing acceptance in the next decade and will ultimately be integrated directly to analytical instruments for the purpose of organic analysis. Work in this direction is in progress. In spite of the fact that many difficulties have already been overcome to deliver on the spectroscopist's dream of "fully automated structure elucidation" there is still work to do. Nevertheless, as the efficiency of expert systems is enhanced the solution of increasingly complex structural problems will be achievable.
Journal of Cheminformatics 01/2009; 1:3. · 3.59 Impact Factor
[show abstract][hide abstract] ABSTRACT: 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. In such cases the initial 2D NMR data are contradictory, and the correct solution is therefore not directly attainable. Unfortunately nonstandard correlations and the number of intervening bonds usually cannot be identified experimentally. In this work we suggest a new approach that we term Fuzzy Structure Generation. This allows the solution of structural problems whose 2D NMR data contain an unknown number of nonstandard correlations having different and unknown lengths. Suggested methods for the application of Fuzzy Structure Generation are described, and their application is illustrated by a series of real-world examples. We conclude that Fuzzy Structure Generation is efficient, and there is no real alternative at present in terms of a universal practical method for the structure elucidation of organic molecules from 2D NMR data.
Journal of Chemical Information and Modeling 01/2007; 47(3):1053-66. · 4.30 Impact Factor
[show abstract][hide abstract] ABSTRACT: 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. Recently, an opinion was expressed in the literature that these systems would fail when elucidating structures containing more than 30 heavy atoms. A suggestion was put forward that stochastic algorithms for structure generation would be necessary to overcome this shortcoming. In this article, we describe a comprehensive investigation of the capabilities of the deterministic expert system Structure Elucidator. The results of performing the structure elucidation of 250 complex natural products with this program were studied and generalized. The conclusion is that 2D NMR deterministic expert systems are certainly capable of elucidating large structures (up to about 100 heavy atoms) and can deal with the complexities associated with both poor and contradictory spectral data.
Journal of Chemical Information and Modeling 01/2006; 46(4):1643-56. · 4.30 Impact Factor
[show abstract][hide abstract] ABSTRACT: The reaction between an alpha,beta-unsaturated pyruvate and ethyl diazoacetate (EDA) yielded two unexpected products. The structures of these products were determined by automated elucidation of the chemical structures using spectroscopic inputs of a series of 1D and 2D NMR data using the computer program ACD/Structure Elucidator, StrucEluc. The formation of these products is rationalised. Their structures were also confirmed by x-ray crystallography.
Magnetic Resonance in Chemistry 08/2004; 42(7):567-72. · 1.53 Impact Factor
[show abstract][hide abstract] ABSTRACT: 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. The use of fragments has frequently transformed very difficult 2D NMR elucidation challenges into easily solvable tasks. A strategy to utilize molecular fragments has been developed and optimized based on specific challenging examples. This strategy will be described here using real world examples. Experience gained by solving more than 150 structure elucidation problems from a variety of literature sources is also reviewed in this work.
Journal of Chemical Information and Computer Sciences 01/2004; 44(3):771-92.
[show abstract][hide abstract] ABSTRACT: 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. Though experimental techniques have recently been described to aid in the identification of the nature of the couplings the detection of whether a coupling is 2-bond or greater still remains a challenge in most laboratories. In the StrucEluc software system the common lengths of the connectivities, 1-bond for COSY and 1- or 2-bond for HMBC, derived from 2D NMR data are set as the default. Therefore, in the presence of any extended connectivities contradictions can appear in the 2D NMR data. In this article, algorithmic methods for the detection and removal of contradictions in 2D NMR data that have been developed in support of StrucEluc are described. The methods are based on the analysis of molecular connectivity diagrams, MCDs. These methods have been implemented in the StrucEluc system and tested by solving 50 structural problems with 2D NMR spectral data containing contradictions. The presence of contradictions was detected by the algorithm in 90% of the cases, and the contradictions were automatically removed in approximately 50% of the problems. A method of "fuzzy" structure generation in the presence of contradictions has been suggested and successfully tested in this work. This work will demonstrate examples of the application of developed methods to a number of structural problems.
Journal of Chemical Information and Computer Sciences 01/2004; 44(5):1737-51.
[show abstract][hide abstract] ABSTRACT: This paper considers the strategy of the StrucEluc expert system application for structure elucidation of new natural products when there is a lack of connectivity information that is characteristic of proton-deficient molecules. It is shown that in this case, a database search for fragments using a 13C NMR spectrum as input allows an investigator to fill gaps in the recorded data. Algorithms and programs have been developed that allow fragments found in the library and/or proposed by the user to be embedded in the molecular connectivities diagrams built on the basis of 2D NMR data analysis. We demonstrate the structure determination of three alkaloids from the cryptolepine series using the principles of construction and application of a user fragment library. The approach described appears to be the most efficient means of structure elucidation for natural products with 2D NMR spectra characterized by sparse responses. Copyright 2003 John Wiley & Sons, Ltd.
Magnetic Resonance in Chemistry. 01/2003; 41(5):359-372.
[show abstract][hide abstract] ABSTRACT: 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. The structures for 75% of the data sets were determined in less than one minute, while 90% of the analyses required no more than 30 minutes. The strategy of structure elucidation by this expert system is described, and several examples are discussed. These illustrate that StrucEluc is a powerful and versatile analytical tool for the structure elucidation of natural products.
Journal of Natural Products 06/2002; 65(5):693-703. · 3.29 Impact Factor