Peer-Reviewed Articles on ACD/Structure Elucidator Suite

Showing 1-30 of 47

Targeted Dereplication of Microbial Natural Products by High-Resolution MS and Predicted LC Retention Time
Apr 26, 2017
J. Chervin, M. Stierhof, M.H. Tong, D. Peace, K. Østnes Hansen, D.S. Urgast, J.H. Andersen, Y. Yu, R. Ebel, K. Kyeremeh, V. Paget, G. Cimpan, A. Van Wyk, H. Deng, M. Jaspars, and J.N. Tabudravu
A new strategy for the identification of known compounds in Streptomyces extracts that can be applied in the discovery of natural products is presented. The strategy incorporates screening a database of 5555 natural products including 5098 structures from Streptomyces sp., using a high-throughput LCMS data processing algorithm that utilizes HRMS data and predicted LC retention times (tR) as filters for rapid identification of known compounds in the natural product extract. The database, named StrepDB, contains for each compound the structure, molecular formula, molecular mass, and predicted LC retention time. All identified compounds are annotated and color coded for easier visualization. It is an indirect approach to quickly assess masses (which are not annotated) that may potentially lead to the discovery of new or novel structures. In addition, a spectral database named MbcDB was generated using the ACD/Spectrus DB Platform. MbcDB contains 665 natural products, each with structure, experimental HRESIMS, MS/MS, UV, and NMR spectra. StrepDB was used to screen a mutant Streptomyces albus extract, which led to the identification and isolation of two new compounds, legonmaleimides A and B, the structures of which were elucidated with the aid of MbcDB and spectroscopic techniques. The structures were confirmed by computer-assisted structure elucidation (CASE) methods using ACD/Structure Elucidator Suite. The developed methodology suggests a pipeline approach to the dereplication of extracts and discovery of novel natural products.
J. Nat. Prod., 2017, 80 (5): 1370-1377


Structure Elucidation Software Review in Magnetic Resonance in Chemistry
Aug 18, 2016
ACD/Labs
The latest edition of Magnetic Resonance in Chemistry features a special introductory tutorial to Computer-Assisted Structure Elucidation (CASE) aimed at undergraduate and graduate students, and utilizes a free CASE tutorial software package available from ACD/Labs.
Structure Elucidation Software Review in Magnetic Resonance in Chemistry


Computer-Assisted Structure Elucidation in Routine Analysis
Jan 26, 2016
P. Wheeler, S. Hayward, M. Elyashberg
The elucidation of unknown structures, especially those with novel moieties found in natural products, often results in initially incorrect published structures, which then require either exhaustive spectroscopic analysis, full chemical synthesis or both to prove the correct structure. In many cases, the initial incorrect structure and subsequent analytical work could be avoided using computer-assisted structure elucidation (CASE).
P. Wheeler, S. Hayward, M. Elyashberg. (2016). Computer-Assisted Structure Elucidation in Routine Analysis. American Laboratory, 48(2): 12–14.


Dereplication of natural products using minimal NMR data inputs
Sep 11, 2015
R.B. Williams, M. O'Neill-Johnson, A.J. Williams, P. Wheeler, R. Pol, A. Moser
In collaboration with Sequoia Sciences Inc., we developed a strategy for the dereplication of a complete or a partial structure using 1H NMR, 1H–13C HSQC and 1H–1H COSY spectral data, a molecular formula composition range and structural fragments against a massive database of about 22 million compounds is considered. The work was based on 18 compounds and was applicable to research on natural products and synthetic compounds.

The research was published in the journal Organic & Biomolecular Chemistry on September 2015 entitled Dereplication of natural products using minimal NMR data input.
R.B. Williams, M. O'Neill-Johnson, A.J. Williams, P. Wheeler, R. Pol, A. Moser. (2015). Dereplication of natural products using minimal NMR data inputs. Org. Biomol. Chem. 13: 9957–9962.


Activity-Independent Discovery of Secondary Metabolites Using Chemical Elicitation and Cheminformatic Inference
Sep 09, 2015
S.M. Pimentel-Elardo, D. Sørensen, L. Ho, M. Ziko, S.A. Bueler, S. Lu, J. Tao, A. Moser, R. Lee, D. Agard, G. Fairn, J.L. Rubinstein, B.K. Shoichet, and J.R. Nodwell
Most existing antibiotics were discovered through screens of environmental microbes, particularly the streptomycetes, for the capacity to prevent the growth of pathogenic bacteria. This “activity-guided screening” method has been largely abandoned because it repeatedly rediscovers those compounds that are highly expressed during laboratory culture. Most of these metabolites have already been biochemically characterized. However, the sequencing of streptomycete genomes has revealed a large number of “cryptic” secondary metabolic genes that are either poorly expressed in the laboratory or that have biological activities that cannot be discovered through standard activity-guided screens. Methods that reveal these uncharacterized compounds, particularly methods that are not biased in favor of the highly expressed metabolites, would provide direct access to a large number of potentially useful biologically active small molecules. To address this need, we have devised a discovery method in which a chemical elicitor called Cl-ARC is used to elevate the expression of cryptic biosynthetic genes. We show that the resulting change in product yield permits the direct discovery of secondary metabolites without requiring knowledge of their biological activity. We used this approach to identify three rare secondary metabolites and find that two of them target eukaryotic cells and not bacterial cells. In parallel, we report the first paired use of cheminformatic inference and chemical genetic epistasis in yeast to identify the target. In this way, we demonstrate that oxohygrolidin, one of the eukaryote-active compounds we identified through activity-independent screening, targets the V1 ATPase in yeast and human cells and secondarily HSP90.
S.M. Pimentel-Elardo et al.. (2015). Activity-Independent Discovery of Secondary Metabolites Using Chemical Elicitation and Cheminformatic Inference. ACS Chem. Biol., 10 (11): 2616–2623


Turning Spiroketals Inside Out: A Rearrangement Triggered by an Enol Ether Epoxidation
Jun 17, 2015
Chris Lorenc, Dr. Josep Saurí, Arvin Moser, Dr. Alexei V. Buevich, Dr. Antony J. Williams, Dr. R. Thomas Williamson, Dr. Gary E. Martin, and Prof. Dr. Mark W. Peczuh
Spiroketals organize small molecule structures into well-defined, three-dimensional configurations that make them good ligands of proteins. We recently discovered a tandem cycloisomerization–dimerization reaction of alkynyl hemiketals that delivered polycyclic, enol-ether-containing spiroketals. Here we describe rearrangements of those compounds, triggered by epoxidation of their enol ethers that completely remodel their structures, essentially turning them “inside out”. Due to the high level of substitution on the carbon skeletons of the substrates and products, characterization resorted to X-ray crystallography and advanced computation and NMR techniques to solve the structures of representative compounds. In particular, a new proton-detected ADEQUATE NMR experiment (1,1-HD-ADEQUATE) enabled the unequivocal assignment of the carbon skeleton of one of the new compounds. Solution of the structures of the representative compounds allowed for the assignment of product structures for the other compounds in two separate series. Both the rearrangement and the methods used for structural determination of the products are valuable tools for the preparation of characterization of new small molecule compounds.
Lorenc, C. et al. (2015) Turning Spiroketals Inside Out: A Rearrangement Triggered by an Enol Ether Epoxidation. ChemstryOpen Online.


Identification and structure elucidation by NMR spectroscopy
Jun 01, 2015
M. Elyashberg
The state of the art and recent developments in application of nuclear magnetic resonance (NMR) for structure elucidation and identification of small organic molecules are discussed. The recently suggested new two-dimensional (2D)-NMR experiments combined with the advanced instrumentation allow structure elucidation of new organic compounds at a sample amount of less than 10 μg. A pure shift approach that provides 1H-decoupled proton spectra drastically simplified 1H and 2D NMR spectra interpretation. The structure elucidation of extremely hydrogen-deficient compounds was dramatically facilitated due to the methodology based on combination of new 2D-NMR experiments providing longrange heteronuclear correlations with computer-assisted structure elucidation (CASE). The capabilities of CASE systems are discussed. The role of NMR-spectrum prediction in structure verification and NMR approaches for qualitative mixture analysis are considered.
M. Elyashberg. (2015). Identification and structure elucidation by NMR spectroscopy. Trends in Analytical Chemistry, 69:88-97


Computer-Assisted Structure Elucidation of Black Chokeberry (Aronia melanocarpa) Fruit Juice Isolates with a New Fused Pentacyclic Flavonoid Skeleton
Jun 01, 2015
C. Benjamin Naman, Jie Li, Arvin Moser, Jeffery M. Hendrycks, P. Annécie Benatrehina, Heebyung Chai, Chunhua Yuan, William J. Keller, and A. Douglas Kinghorn
Melanodiol 4''-O-protocatechuate (1) and melanodiol (2) represent novel flavonoid derivatives isolated from a botanical dietary supplement ingredient, dried black chokeberry (Aronia melanocarpa) fruit juice. These noncrystalline compounds possess an unprecedented fused pentacyclic core with two contiguous hemiketals. Due to having significant hydrogen deficiency indices, their structures were determined using computer-assisted structure elucidation software. The in vitro hydroxyl radical-scavenging and quinone reductase-inducing activity of each compound are reported, and a plausible biogenetic scheme is proposed.
Naman, C.B et al. (2015) Computer-Assisted Structure Elucidation of Black Chokeberry (Aronia melanocarpa) Fruit Juice Isolates with a New Fused Pentacyclic Flavonoid Skeleton. Org. Lett. Online.


Computer-Based Structure Elucidation from Spectral Data
May 21, 2015
M.E. Elyashberg, A.J. Williams
Here, the authors introduce readers to solving molecular structure elucidation problems using the expert system ACD/Structure Elucidator. They explain in detail the concepts of the Computer-Assisted Structure Elucidation (CASE) approach and point out the crucial role of understanding the axiomatic nature of the data used to deduce the structure. Aspects covered include the main blocks of the expert system and essential features of the mathematical algorithms used. Graduate and PhD students as well as practicing chemists are provided with a detailed explanation of the various practical approaches depending on available spectral data peculiarities and the complexity of the unknown structure. This is supported by a large number of real-world completed examples, most of which are related to the structure elucidation of natural product molecules containing unusual skeletons. Dedicated software and further supplementary material are available at www.acdlabs.com/TeachingSE.
Elyashberg, M.E., Williams, A.J. (2015) Computer-Based Structure Elucidation from Spectral Data. Springer-Verlag Berlin Heidelberg.


Nuclear Magnetic Resonance in the Structural Elucidation of Natural Products
Oct 21, 2014
William F. Reynolds, Eugene P. Mazzola
From its modest beginnings in the 1950s, nuclear magnetic resonance (NMR) spectroscopy has become the premier analytical tool for the determination of structure of organic natural products. Structural elucidation efforts were originally limited to proton NMR and typically required both relatively large quantities of material and considerable time. However, modern NMR spectrometers, with an array of one- and two-dimensional experiments, permit the structures of complex organic molecules to be determined, often in a day, using less than 1 mg of sample. This chapter will prepare natural product chemists to employ modern NMR techniques effectively in the determination of molecular structures. It focuses on the rapid determination of whether an isolated compound is known or new, the information content of various two-dimensional and selective one-dimensional NMR experiments, the use of these experiments in combination and avoiding or overcoming common pitfalls in determining molecular structures, the selection of optimum acquisition parameters and data processing methods and parameters, and the use of computer-assisted structure elucidation.
Reynolds, W.F., Mazzola, E.P. (2015). Nuclear Magnetic Resonance in the Structural Elucidation of Natural Products. In A.D. Kinghorn, H. Falk, J. Kobayashi (Eds.), Progress in the Chemistry of Organic Natural Products (223–309). Springer International Publishing Switzerland


Structure Revision of Asperjinone Using Computer-Assisted Structure Elucidation Methods
Jan 04, 2013
M. Elyashberg, K. Blinov, S. Molodtsov, A.J. Williams
The elucidated structure of asperjinone, a natural product isolated from thermophilic Aspergillus terreus, was revised using the expert system Structure Elucidator. The reliability of the revised structure was confirmed using 180 structures containing the (3,3-dimethyloxiran-2-yl)methyl fragment as a basis for comparison and whose chemical shifts contradict the suggested structure.
J. Nat. Prod., 76:113-116, 2013


Using a combination of atomic force microscopy and computer assisted structure elucidation to determine the structure of bjørnøyoxazole, a highly modified halogenated dipeptide from the Arctic hydrozoan Thuiaria breitfussi
Dec 03, 2012
K.Ѳ. Hanssen, B. Schuler, A..J. Williams, T. B. Demissie, E. Hansen, J. H. Andersen, J. Svenson, K. Blinov, M. Repisky, F. Mohn, G. Meyer, J.-S. Svendsen, K. Ruud, M. Elyashberg, L.Gross, M. Jaspars, and J. Isaksson
Turning a new leaf: The first structures isolated from Thuiaria breitfussi, the breitfussins, are presented. This structural class consists of indole–oxazole–pyrrole units. Limited quantities prevented crystallization; therefore, the structures were solved using a novel combination of AFM, computer-aided structure elucidation (CASE), and DFT calculations. Visualization by AFM determined all the connection points of the cyclic systems and the other substituents.
Angew. Chem. Int. Ed.. 51(49):12238-12241,2012


Heterocyclization of electrophilic alkenes with tetranitromethane revisited: regiochemistry and the mechanism of nitroisoxazole formation
Mar 21, 2012
E.B. Averina, Y.V. Samoilichenko, Y.A. Volkova, Y.K. Grishin, V.B. Rybakov, A.G. Kutateladze, M.E. Elyashberg, T.S. Kuznetsova, N. S. Zefirov
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.
Tetrahedron Letters, 53(12):1472–1475, 2012


Blind trials of Computer-Assisted Structure Elucidation software
Feb 01, 2012
A. Moser, M. Elyashberg, A.J Williams, K.A. Blinov, J. DiMartino
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. An effective structure elucidation software technology aims to mimic the skills of a human in interpreting the complex nature of spectral data while producing a solution within a reasonable amount of time. This type of software is known as computer-assisted structure elucidation or CASE software. A systematic trial of the ACD/Structure Elucidator CASE software was conducted over an extended period of time by analysing a set of single and double-blind trials submitted by a global audience of scientists. The purpose of the blind trials was to reduce subjective bias. Double-blind trials comprised of data where the candidate compound was unknown to both the submitting scientist and the analyst. The level of expertise of the submitting scientist ranged from novice to expert structure elucidation specialists with experience in pharmaceutical, industrial, government and academic environments.
J. Cheminf. 4(5), 2012


Elucidating "Undecipherable" Chemical Structures Using Computer Assisted Structure Elucidation Approaches
Jan 01, 2012
5. M.E. Elyashberg, K.A. Blinov, S.G. Molodtsov, A.J. Williams
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.
Magn. Reson. Chem., 50:22-27, 2012


Contemporary Computer-Assisted Approaches to Molecular Structure Elucidation
Nov 30, 2011
M.E. Elyashberg, A. Williams, K. Blinov
Computer-Assisted Structure Elucidation (CASE) systems are a combination of software algorithms and tools to support and enable chemists and spectroscopists engaged in the process of molecular structure elucidation via the analysis of spectroscopic data. These expert systems dramatically reduce the time associated with structure elucidation and improve the reliability of the results. Contemporary Computer-Assisted Approaches to Molecular Structure Elucidation describes the principles on which these expert systems for spectroscopic structure elucidation are based and concisely explains the algorithmic concepts behind the programs. The authors use their own personal experiences in the development of the Structure Elucidator (StrucEluc) CASE software system to discuss the present state-of-the-art in computer-assisted structure elucidation. Scientists that are presently using CASE systems will be interested in the algorithms and modern approaches and for organizations that are currently using the StrucEluc platform the book is designed to help researchers understand the strategies behind CASE as well as details regarding the StrucEluc platform. For scientists that have never used CASE systems they will now have access to all necessary information to understand CASE systems for mastering this new and very effective approach to structure elucidation. The authors overall goal is writing this book is to produce the 'must read' definitive text that will represent the results of decades of work to develop computer-assisted structure elucidation software systems. CASE systems are now powerful software tools commonly outperforming and correcting human interpretations of data. This book will also provide an historical perspective of the work of the founding fathers of the technique and identify the challenges that have been overcome to produce modern CASE systems.
M.E. Elyashberg, A. Williams, K. Blinov. Edited by William Price. RSC Publishing, 2012


Enhanced automated structure elucidation by inclusion of two-bond specific data
Aug 01, 2010
6. S.F. Cheatham, M. Kline, R. R. Sasaki, K. A. Blinov, M. E. Elyashberg. S. G. Molodtsov
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.
Magn. Reson. Chem., 48:571-574, 2010


Structural revisions of natural products by Computer Assisted Structure Elucidation (CASE) Systems
May 18, 2010
M. Elyashberg, A. Williams, K. Blinov
Nat. Prod. Rep., 27(9):1296-1328, 2010


Empirical and DFT GIAO quantum-mechanical methods of 13C chemical shifts prediction: competitors or collaborators?
Jan 27, 2010
8. M. Elyashberg, K. Blinov, Y. Smurnyy, T. Churanova and A. Williams
The accuracy of 13C chemical shift prediction by both DFT GIAO quantum-mechanical (QM) and empirical methods was compared using 205 structures for which experimental and QM-calculated chemical shifts were published in the literature. For these structures, 13C chemical shifts were calculated using HOSE code and neural network (NN) algorithms developed within our laboratory. In total, 2531 chemical shifts were analyzed and statistically processed. It has been shown that, in general, QM methods are capable of providing similar but inferior accuracy to the empirical approaches, but quite frequently they give larger mean average error values. For the structural set examined in this work, the following mean absolute errors (MAEs) were found: MAE(HOSE) = 1.58 ppm, MAE(NN) = 1.91 ppm and MAE(QM) = 3.29 ppm. A strategy of combined application of both the empirical and DFT GIAO approaches is suggested. The strategy could provide a synergistic effect if the advantages intrinsic to each method are exploited.
Magn. Reson. Chem., 48(3):219-229, 2010.


Development of a fast and accurate method of NMR chemical shift prediction
May 15, 2009
K. Blinov, Y.D. Smurnyy, T.S. Churanova, M. Elyashberg, A.J. Williams
In this article we describe a fast and accurate method of 13C NMR chemical shift prediction. The high speed of chemical shift calculation described is achieved using a simple structure description scheme based on individual atoms rather than functional groups. The systematic choice of an appropriate encoding scheme and the usage of partial least squares regression on a large training set has resulted in a robust and fast algorithm. The approach provides accuracy comparable with other well known approaches but demonstrates accelerated calculation speeds of up to a thousand times faster.
Chemometr. Intell. Lab. Syst., 97:91-97, 2009


Applications of Computer-Aided Methods of Structure Elucidation to the Revision of Chemical Structures. I. Structure Revision of Lamellarin γ
Mar 18, 2009
M. E. Elyashberg, K. A. Blinov, S.G. Molodtsov, T.S. Churanova, A.J. Williams
The structure elucidation of new organic compounds is clearly one of the most common challenges for organic chemistry and the application of spectroscopy. Molecular structures are usually established on the basis of the combined treatment of data obtained from MS, NMR, IR and UV spectra. Among the various spectroscopic methods 2D NMR spectroscopy now plays an outstanding role in the process of structure determination and is a rich source of structural information. This information however is fuzzy by nature [1], and different researchers can interpret the data in different ways. As a result, it is quite common that structures published in the literature by one group of researchers can be revised by another group. It can be expected that the number of incorrectly identified structures may be reduced if Computer Assisted Structure Elucidation systems (CASE) are used for the purpose of structure elucidation.
ChemSpider J. Chem., 2009


Computer-assisted methods for molecular structure elucidation: realizing a spectroscopist's dream
Mar 17, 2009
M. Elyashberg, K. Blinov, S. Molodtsov, Y. Smurnyy, A. Williams, T. Churanova
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.
J. Cheminf., 1(3), 2009


The application of empirical methods of 13C NMR chemical shift prediction as a filter for determining possible relative stereochemistry
Feb 10, 2009
M. Elyashberg, K. Blinov, A.J. Williams
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.
Magn. Reson. Chem., 47:333-341, 2009.


A systematic approach for the generation and verification of structural hypotheses
Feb 05, 2009
11. M. Elyashberg, K. Blinov, A.J. Williams
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.
Magn. Reson. Chem., 47:371-389, 2009.


Computer-assisted structure verification and elucidation tools in NMR-based structure elucidation
Jul 01, 2008
M.E. Elyashberg, A.J. Williams, G.E. Martin
The intent of this review is to provide an overview of the current state-of-the-art in the field of computer-aided structure elucidation and verification. In this work, numerous examples of the automated elucidation of complex structures of natural products will define the present capabilities of existing expert systems. The future of CASE systems, in our opinion, remains one of great value and has the potential to definitively contribute to higher throughput in laboratories around the world as well as providing support to skilled spectroscopists challenged with complex elucidations and facilitating structure verification and elucidation for organic chemists utilizing openaccess systems.
Progress in NMR spectroscopy, 53 (1/2):1-104, 2008.


The Performance Validation of Neural Network Based 13C NMR Prediction Using a Publicly Available Data Source
Feb 28, 2008
K.A. Blinov, Y.D. Smurnyy, M.E. Elyashberg, T.S. Churanova, M. Kvasha, C. Steinbeck, B.E. Lefebvre, A.J Williams
The validation of the performance of a neural network based 13C NMR prediction algorithm using a test set available from an open source publicly available database, NMRShiftDB, is described. The validation was performed using a version of the database containing ca. 214 000 chemical shifts as well as for two subsets of the database to compare performance when overlap with the training set is taken into account. The first subset contained ca. 93 000 chemical shifts that were absent from the ACD/CNMR DB, the “excluded shift set” used for training of the neural network and the ACD/CNMR prediction algorithm, while the second contained ca. 121 000 shifts that were present in the ACD/CNMR DB training set, the “included shift set”. This work has shown that the mean error between experimental and predicted shifts for the entire database is 1.59 ppm, while the mean deviation for the subset with included shifts is 1.47 and 1.74 ppm for excluded shifts. Since similar work has been reported online for another algorithm we compared the results with the errors determined using Robien's CNMR Neural Network Predictor using the entire NMRShiftDB for program validation.
J. Chem. Informat. Model., 48:550-555, 2008


Applying computer assisted structure elucidation algorithms for the purpose of structure validation–revisiting the NMR assignments of hexacyclinol
Feb 08, 2008
A.J. Williams, M. Elyashberg, K.A. Blinov, D.C. Lankin, G.E. Martin, W.F. Reynolds, J.A. Jr. Porco, C.A. Singleton S. Su
Computer-assisted structure elucidation (CASE) using a combination of 1D and 2D NMR data has been available for a number of years. These algorithms can be considered as “logic machines” capable of deriving all plausible structures from a set of structural constraints or “axioms”, defined by the spectroscopic data and associated chemical information or prior knowledge. CASE programs allow the spectroscopist not only to determine structures from spectroscopic data but also to study the dependence of the proposed structure on changes to the set of axioms. In this article, we describe the application of the ACD/Structure Elucidator expert system to help resolve the conflict between two different hypothetical hexacyclinol structures derived by different researchers from the NMR spectra of this complex natural product. It has been shown that the combination of algorithms for both structure elucidation and structure validation delivered by the expert system enables the identification of the most probable structure as well as the associated chemical shift assignments.
J. Nat. Prod., 71:581–588, 2008


New Computer-Assisted Methods for the Elucidation of Molecular Structure from 2-D Spectra
Jan 01, 2008
18. M.E. Elyashberg, K.A. Blinov, S.G. Molodtsov and E.D. Smurnyi
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.
J. Anal. Chem., 63(1):13–20, 2008


Toward More Reliable 13C And 1H Chemical Shift Prediction: Systematic Comparison Of Neural Network And Least Squares Regression Based Approaches
Jan 01, 2008
Y.D. Smurnyy, K.A. Blinov, M.E. Elyashberg, T.S. Churanova, A.J. Williams
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. Both of the methods, least-squares and neural network analyses, produce results of a very similar quality, but the least-squares algorithm is approximately 2−3 times faster.
J. Chem. Informat. Model., 48:128-134, 2008


Fuzzy Structure Generation: A New Efficient Tool For Computer-Aided Structure Elucidation (CASE)
Apr 11, 2007
M. Elyashberg, K.A. Blinov, A.J. Williams, S.G. Molodtsov, G.E. Martin
Contemporary Computer-Aided Structure Elucidation (CASE) systems are heavily based on the utilization of 2D NMR spectra. The utilization of HMBC/GHMBC and COSY/COSY correlations generally assumes that these correlations result from 2-3JCH and 2-3JHH spin couplings, respectively, and consequently these values are used as the default setting in these systems. Our previous studies [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 Generations is efficient and there is no real alternative at present in terms of a universal practical method for the structure elucidation of organic molecules form 2D NMR data.
J. Chem. Inform. Model., 47:1053-1066, 2007