Computer-assisted methods for molecular structure elucidation: realizing a spectroscopist's dream

BackgroundThis 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.ResultsThe 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.ConclusionThe 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.

[1]  Bruce G. Buchanan,et al.  Applications of artificial intelligence for chemical inference. I - The number of possible organic compounds - Acyclic structures containing C, H, O, and N. , 1969 .

[2]  M. Elyashberg,et al.  The application of empirical methods of 13C NMR chemical shift prediction as a filter for determining possible relative stereochemistry , 2009, Magnetic resonance in chemistry : MRC.

[3]  A J Williams,et al.  Applying computer-assisted structure elucidation algorithms for the purpose of structure validation: revisiting the NMR assignments of hexacyclinol. , 2008, Journal of natural products.

[4]  Antony J. Williams,et al.  A systematic approach for the generation and verification of structural hypotheses , 2009, Magnetic resonance in chemistry : MRC.

[5]  M. Elyashberg,et al.  An expert system for automated structure elucidation utilizing 1H-1H, 13C-1H and 15N-1H 2D NMR correlations , 2001, Fresenius' journal of analytical chemistry.

[6]  M. E. Elyashberg,et al.  Computer-aided determination of relative stereochemistry and 3D models of complex organic molecules from 2D NMR spectra , 2005 .

[7]  Kurt Wüthrich,et al.  NOBEL LECTURE: NMR Studies of Structure and Function of Biological Macromolecules , 2003, Bioscience reports.

[8]  Christoph Steinbeck,et al.  Performance Validation of Neural Network Based 13C NMR Prediction Using a Publicly Available Data Source , 2008, J. Chem. Inf. Model..

[9]  Antony J. Williams,et al.  Identification of degradants of a complex alkaloid using NMR cryoprobe technology and ACD/structure elucidator , 2002 .

[10]  Antony J. Williams,et al.  Computer‐assisted structure elucidation of natural products with limited 2D NMR data: application of the StrucEluc system , 2003 .

[11]  Dorothea Heiss-Czedik,et al.  An Introduction to Genetic Algorithms. , 1997, Artificial Life.

[12]  David Neuhaus,et al.  The Nuclear Overhauser Effect in Structural and Conformational Analysis , 1989 .

[13]  Antony J. Williams,et al.  Automated structure elucidation — the benefits of a symbiotic relationship between the spectroscopist and the expert system , 2003 .

[14]  Antony J. Williams,et al.  Toward More Reliable 13C and 1H Chemical Shift Prediction: A Systematic Comparison of Neural-Network and Least-Squares Regression Based Approaches , 2008, J. Chem. Inf. Model..

[15]  V. Mamedov,et al.  Application of theoretically computed chemical shifts to structure determination of novel heterocyclic compounds , 2006 .

[16]  Antony J. Williams,et al.  Structure Elucidation from 2D NMR Spectra Using the StrucEluc Expert System: Detection and Removal of Contradictions in the Data , 2004, J. Chem. Inf. Model..

[17]  J. Nuzillard,et al.  Logic for structure determination , 1991 .

[18]  Antony J. Williams,et al.  Application of a new expert system for the structure elucidation of natural products from their 1D and 2D NMR data. , 2002, Journal of natural products.

[19]  S. Rychnovsky Predicting NMR spectra by computational methods: structure revision of hexacyclinol. , 2006, Organic letters.

[20]  M. Munk,et al.  The role of two-dimensional nuclear magnetic resonance spectroscopy in computer-enhanced structure elucidation , 1991 .

[21]  Sergey G. Molodtsov,et al.  Structure Elucidator: A Versatile Expert System for Molecular Structure Elucidation from 1D and 2D NMR Data and Molecular Fragments , 2004 .

[22]  M. Elyashberg,et al.  Quantitative molecular analysis by infrared spectrometry without standard materials , 1995 .

[23]  Jochen Junker,et al.  2D‐NMR‐Guided Constitutional Analysis of Organic Compounds Employing the Computer Program COCON[#] , 1999 .

[24]  Antony J. Williams,et al.  Structure Elucidator: A Versatile Expert System for Molecular Structure Elucidation from 1D and 2D NMR Data and Molecular Fragments , 2004, J. Chem. Inf. Model..

[25]  Kimito Funatsu,et al.  Recent Advances in the Automated Structure Elucidation System, CHEMICS. Utilization of Two-Dimensional NMR Spectral Information and Development of Peripheral Functions for Examination of Candidates , 1996, J. Chem. Inf. Comput. Sci..

[26]  James J La Clair Total syntheses of hexacyclinol, 5-epi-hexacyclinol, and desoxohexacyclinol unveil an antimalarial prodrug motif. , 2006, Angewandte Chemie.

[27]  M. Elyashberg,et al.  Expert systems as a tool for the molecular structure elucidation by spectral methods. Strategies of solution to the problems , 1997 .

[28]  M. Elyashberg Expert systems for structure elucidation of organic molecules by spectral methods , 2000 .

[29]  Vladimír Jakuš Artificial Intelligence in Chemistry , 1992 .

[30]  M. Elyashberg,et al.  X-PERT: a user-friendly expert system for molecular structure elucidation by spectral methods , 1997 .

[31]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[32]  Antony J. Williams,et al.  Are Deterministic Expert Systems for Computer-Assisted Structure Elucidation Obsolete? , 2006, J. Chem. Inf. Model..

[33]  M. Elyashberg,et al.  Quindolinocryptotackieine: the elucidation of a novel indoloquinoline alkaloid structure through the use of computer‐assisted structure elucidation and 2D NMR , 2003 .

[34]  W. Reynolds,et al.  New cembranes from Cleome spinosa. , 2004, Journal of natural products.

[35]  B. Jayaprakasam,et al.  Ashwagandhanolide, a bioactive dimeric thiowithanolide isolated from the roots of Withania somnifera. , 2006, Journal of natural products.

[36]  M. Munk,et al.  Alanylactinobicyclone. Application of computer techniques to structure elucidation , 1969 .

[37]  Joshua Lederberg,et al.  Applications of Artificial Intelligence for Organic Chemistry: The DENDRAL Project , 1980 .

[38]  M. Elyashberg,et al.  A new approach to computer-aided molecular structure elucidation: the expert system Structure Elucidator , 1999 .

[39]  Alessandro Bagno,et al.  Toward the complete prediction of the 1H and 13C NMR spectra of complex organic molecules by DFT methods: application to natural substances. , 2006, Chemistry.

[40]  Barbara Kappes,et al.  Hexacyclinol, a new antiproliferative metabolite of Panus rudis HKI 0254. , 2002, The Journal of antibiotics.

[41]  Neil A. B. Gray,et al.  Computer-assisted structure elucidation , 1986 .

[42]  J. Clerc,et al.  Computer-Aided Identification of Organic Molecules by their Molecular Spectra , 1979 .

[43]  Giuseppe Bifulco,et al.  Structure validation of natural products by quantum-mechanical GIAO calculations of 13C NMR chemical shifts. , 2002, Chemistry.

[44]  H. Ge,et al.  Bioactive oligostilbenoids from the stem bark of Hopea exalata. , 2006, Journal of natural products.

[45]  Kurt Wüthrich,et al.  NMR studies of structure and function of biological macromolecules (Nobel lecture). , 2003, Angewandte Chemie.

[46]  N. Gray Artificial intelligence in chemistry , 1988 .

[47]  Shun Su,et al.  Total synthesis and structure assignment of (+)-hexacyclinol. , 2006, Angewandte Chemie.

[48]  Christoph Steinbeck,et al.  LUCY—A Program for Structure Elucidation from NMR Correlation Experiments , 1996 .

[49]  I. Yoo,et al.  Boletunones A and B, highly functionalized novel sesquiterpenes from Boletus calopus. , 2004, Organic letters.

[50]  Martin Will,et al.  Fully Automated Structure Elucidation - A Spectroscopist's Dream Comes True , 1996, J. Chem. Inf. Comput. Sci..

[51]  Antony J. Williams,et al.  Computer-Assisted Structure Verification and Elucidation Tools in NMR-based Structure Elucidation , 2008 .

[52]  Z. Hippe,et al.  Computer Retrieval of Spectral Data , 1980 .

[53]  Mikhail E. Elyashberg,et al.  Development of a fast and accurate method of 13 C NMR chemical shift prediction , 2009 .

[54]  Chen Peng,et al.  Efficient Application of 2D NMR Correlation Information in Computer-Assisted Structure Elucidation of Complex Natural Products , 1994, J. Chem. Inf. Comput. Sci..

[55]  Luis Echegoyen,et al.  Cover Picture: Retro-Cycloaddition Reaction of Pyrrolidinofullerenes (Angew. Chem. Int. Ed. 1/2006) , 2006 .

[56]  Antony J. Williams,et al.  Fuzzy Structure Generation: A New Efficient Tool for Computer-Aided Structure Elucidation (CASE) , 2007, J. Chem. Inf. Model..

[57]  E. Feigenbaum,et al.  Applications of artificial intelligence for chemical inference. I. Number of possible organic compounds. Acyclic structures containing carbon, hydrogen, oxygen, and nitrogen , 1969 .

[58]  A. Derome,et al.  Modern Nmr Techniques for Chemistry Research , 1987 .

[59]  S. Sasaki,et al.  Automated structure elucidation of several kinds of aliphatic and alicyclic compounds , 1968 .