Skip to main content
SpringerLink
Log in

Computer Tools for Structure Elucidation in Effect-Directed Analysis

  • Chapter
  • First Online:
Effect-Directed Analysis of Complex Environmental Contamination

Part of the book series: The Handbook of Environmental Chemistry ((HEC,volume 15))

Abstract

The identification of unknown compounds isolated during Effect-Directed Analysis (EDA) is often a hurdle on the way to the successful outcome of these studies. Ever-improving separation, analytical, and biological techniques allow the isolation of more compounds and effects; however, not all of the compounds contributing to sample toxicity are easily identified. The advancement of database search strategies and publishing of online databases has improved tentative identification of many compounds in recent years, but many chemicals and their transformation products are still not captured within such databases. Structure generation, where the analytical information is used to identify substructures present and absent, provides an alternative strategy to database searching. Where multiple structures matching an unknown spectrum are possible, candidate selection becomes critical to successful identification. The main steps in candidate identification and selection are discussed in this chapter, including examples of programs and strategies available. Improvements in the ability to share data between institutes and the selection criteria for candidate structures are needed to take advantage of recent analytical developments and further enhance structure elucidation in EDA studies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

ACD:

Advanced Chemistry Development Inc.

AMDIS:

Automated Mass Spectral Deconvolution and Identification System

AQI:

Assignment Quality Index

BP:

Boiling Point

CAS Number:

Chemical Abstract Services Registry Number

Da:

Dalton (atomic mass unit)

EDA:

Effect-Directed Analysis

EI-MS:

Electron Impact Mass Spectrometry

EEI:

Even Electron Ions

ElCoCo:

Elemental Composition Computation

EMPOMASS:

Database of Mass Spectra of Unknown or Provisionally Identified Substances (NORMAN)

ESI–FT–MS:

Electrospray Ionization–Fourier Transform–Mass Spectrometry

ESI–QToF-MS:

Electrospray Ionization–Quadrupole Time-of-Flight Mass Spectrometry

GS–MS:

Gas Chromatography–Mass Spectrometry

2HA:

2-hydroxy-9,10-anthraquinone

HR-MS:

High Resolution Mass Spectrometry

IQ:

2-amino-3-methyl-3H-imidazo(4,5-f)quinoline

K:

Kelvin

KRI:

Kovat’s Retention Index

LC:

Liquid Chromatography

LSERs:

Linear Solvation Energy Relationships

LRI:

Lee Retention Index

“M”-peak:

Mass Spectrometric Molecular Ion Mass Peak

MALDI–ToF-MS:

Matrix-Assisted Laser Desorption/Ionization–Time-of-Flight Mass Spectrometry

MODELKEY:

Models for Assessing and Forecasting the Impact of Environmental Key Pollutants on Marine and Freshwater Ecosystems and Biodiversity (EU project)

MOLGEN:

Molecular Structure Generator

MS:

Mass Spectrometry

MS-MS:

Tandem Mass Spectrometry

MSn :

Multistage Mass Spectrometry

MV:

Match Value

m/z:

Mass-to-charge ratio

1NP:

1-nitropyrene

NIST:

National Institute of Standards and Technology

NORMAN:

Network of Reference Laboratories for Emerging Pollutants

OEI:

Odd Electron Ions

PAH:

Polycyclic Aromatic Hydrocarbons

QPID:

Quality Peak Identification Database

QSAR:

Quantitative Structure-Activity Relationship

Q-ToF:

Quadrupole Time-of-Flight Spectrometry

RDB:

Ring and Double Bond

RI:

Retention Index

RP-HPLC:

Reversed Phase High Performance Liquid Chromatography

TIE:

Toxicity Identification Evaluation

References

  1. Brack W (2003) Effect-directed analysis: a promising tool for the identification of organic toxicants in complex mixtures? Anal Bioanal Chem 377:397–407

    Article  CAS  Google Scholar 

  2. NIST/EPA/NIH (2008) NIST Mass Spectral Library. National Institute of Standards and Technology, US Secretary of Commerce, USA

    Google Scholar 

  3. Wiley (2010) Wiley registry of mass spectral data, 9th edn. Wiley, New York

    Google Scholar 

  4. Schymanski EL, Meinert C, Meringer M, Brack W (2008) The use of MS classifiers and structure generation to assist in the identification of unknowns in effect-directed analysis. Anal Chim Acta 615:136–147

    Article  CAS  Google Scholar 

  5. Schymanski E, Bataineh M, Goss K-U, Brack W (2009) Integrated analytical and computer tools for structure elucidation in effect-directed analysis. Trends Anal Chem 28:550–561

    Article  CAS  Google Scholar 

  6. McLafferty FW, Turecek F (1993) Interpretation of mass spectra. University Science Books, Mill Valley, CA

    Google Scholar 

  7. Munk ME (1998) Computer-based structure determination: then and now. J Chem Inf Comput Sci 38:997–1009

    CAS  Google Scholar 

  8. Liao WT, Draper WM, Perera SK (2008) Identification of unknowns in atmospheric pressure ionization mass spectrometry using a mass to structure Search Engine. Anal Chem 80:7765–7777

    Article  CAS  Google Scholar 

  9. Lehotay SJ, Mastovska K, Amirav A, Fialkov AB, Martos PA, Ad K, Fernández-Alba AR (2008) Identification and confirmation of chemical residues in food by chromatography-mass spectrometry and other techniques. Trends Anal Chem 27:1070–1090

    Article  CAS  Google Scholar 

  10. ChemIndex (2010) http://www.chemindex.com/. Accessed: 16/03/2010. ChemIndex

  11. CambridgeSoft (2010) ChemINDEX http://www.cambridgesoft.com/databases/details/?db=7. Accessed: 16/03/2010. CambridgeSoft, Inc

  12. RSC (2010) ChemSpider http://www.chemspider.com. Accessed: 16/03/2010. Royal Society of Chemistry

  13. CambridgeSoft (2010) The Merck Index http://www.cambridgesoft.com/databases/details/?db=1. Accessed: 16/03/2010. CambridgeSoft, Inc

  14. NIST (2008) NIST Chemistry WebBook http://webbook.nist.gov/chemistry/. Accessed: National Institute of Standards and Technology, U.S. Secretary of Commerce

  15. NCBI (2010) PubChem http://pubchem.ncbi.nlm.nih.gov/. Accessed: 16/03/2010. National Center for Biotechnology Information

  16. Polettini A, Gottardo R, Pascali JP, Tagliaro F (2008) Implementation and performance evaluation of a database of chemical formulas for the screening of pharmaco/toxicologically relevant compounds in biological samples using electrospray ionization-time-of-flight mass spectrometry. Anal Chem 80:3050–3057

    Article  CAS  Google Scholar 

  17. Brack W, Bakker J, de Deckere E, Deerenberg C, van Gils J, Hein M, Jurajda P, Kooijman B, Lamoree M, Lek S, de Alda MJL, Marcomini A, Munoz I, Rattei S, Segner H, Thomas K, von der Ohe PC, Westrich B, de Zwart D, Schmitt-Jansen M (2005) MODELKEY – models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity. Environ Sci Pollut Res 12:252–256

    Article  CAS  Google Scholar 

  18. Weiss JM, Hamers T, Thomas KV, van der Linden S, Leonards PEG, Lamoree MH (2009) Masking effect of anti-androgens on androgenic activity in European river sediment unveiled by effect-directed analysis. Anal Bioanal Chem 394:1385–1397

    Article  CAS  Google Scholar 

  19. NIST (2005) Automated mass spectral deconvolution and identification system (AMDIS). National Institute of Standards and Technology (NIST), US Department of Defense, USA

    Google Scholar 

  20. NORMAN (2010) Network of reference laboratories for monitoring of emerging environmental pollutants http://www.norman-network.net. Accessed: 02/08/2010. NORMAN Network

  21. NORMAN (2010) EMPOMASS: database of mass spectra of unknown and provisionally identified substances http://www.normandata.eu/empomass_index.php. (accessed: 02/08/2010)

  22. Horai H, Arita M, Kanaya S, Nihei Y, Ikeda T, Suwa K, Ojima Y, Tanaka K, Tanaka S, Aoshima K, Oda Y, Kakazu Y, Kusano M, Tohge T, Matsuda F, Sawada Y, Hirai MY, Nakanishi H, Ikeda K, Akimoto N, Maoka T, Takahashi H, Ara T, Sakurai N, Suzuki H, Shibata D, Neumann S, Iida T, Funatsu K, Matsuura F, Soga T, Taguchi R, Saito K, Nishioka T (2010) MassBank: a public repository for sharing mass spectral data for life sciences. J Mass Spectrom 45:703–714

    Article  CAS  Google Scholar 

  23. Eisai (2010) Mass++ http://masspp.jp/. Accessed: 02/08/2010. Eisai Ltd

  24. Nesvizhskii AI, Vitek O, Aebersold R (2007) Analysis and validation of proteomic data generated by tandem mass spectrometry. Nat Methods 4:787–797

    Article  CAS  Google Scholar 

  25. Hummel J, Strehmel N, Selbig J, Walther D, Kopka J (2010) Decision tree supported substructure prediction of metabolites from GC–MS profiles. Metabolomics 6:322–333

    Article  CAS  Google Scholar 

  26. Benecke C, Grüner T, Kerber A, Laue R, Wieland T (1997) MOLecular structure GENeration with MOLGEN, new features and future developments. Fresenius J Anal Chem 359:23–32

    Article  CAS  Google Scholar 

  27. Gugisch R, Kerber A, Kohnert A, Laue R, Meringer M, Rücker C, Wassermann A (2010) MOLGEN 5.0 www.molgen.de. Accessed: 02/08/2010

  28. Varmuza K, Stancl F, Lohninger H, Werther W (1996) Short Communication: automatic recognition of substance classes from data obtained by gas chromatography/mass spectroscopy. Lab Autom Inf Manage 31:225–230

    Article  CAS  Google Scholar 

  29. Varmuza K, Werther W (1996) Mass spectral classifiers for supporting systematic structure elucidation. J Chem Inf Comput Sci 36:323–333

    CAS  Google Scholar 

  30. Kerber A, Laue R, Meringer M, Varmuza K (2001) MOLGEN-MS: evaluation of low resolution electron impact mass spectra with MS classification and exhaustive structure generation. Adv Mass Spectrom 15:939–940

    CAS  Google Scholar 

  31. ACD (2007) MS Manager 11.01. Advanced Chemistry Development, Toronto, ON

    Google Scholar 

  32. Krompiec M, Patiny L (2003) ChemCalc http://www.chemcalc.org. Accessed: 17/03/2010. Silesian University of Technology, Poland, University of Lausanne, Switzerland

  33. ThermoFisher (2008) Xcalibur 2.0.7 SP1. Thermo Fisher Scientific Inc

    Google Scholar 

  34. Goodman JM (2009) University of Cambridge Molecular Formula Search http://www-jmg.ch.cam.ac.uk/tools/magnus/EadFormW.html. Accessed: 17/03/2010. Department of Chemistry, University of Cambridge, UK

  35. Foundation PS (2006) Python. Python Software Foundation

    Google Scholar 

  36. Heinonen M, Rantanen A, Mielikainen T, Kokkonen J, Kiuru J, Ketola RA, Rousu J (2008) FiD: a software for ab initio structural identification of product ions from tandem mass spectrometric data. Rapid Commun Mass Spectrom 22:3043–3052

    Article  CAS  Google Scholar 

  37. HighChem (2007) Mass Frontier 5.0. HighChem Ltd./Thermo Scientific

    Google Scholar 

  38. Meringer M (2009) MOLGEN-MSF. M. Meringer, Munich

    Google Scholar 

  39. Schymanski E, Meringer M, Brack W (2009) Matching structures to mass spectra using fragmentation patterns – are the results as good as they look? Anal Chem 81:3608–3617

    Article  CAS  Google Scholar 

  40. Rostad CE, Pereira WE (1986) Kovats and Lee retention indexes determined by gas chromatography/mass spectrometry for organic-compounds of environmental interest. J High Resolut Chromatogr Chromatogr Commun 9:328–334

    Article  CAS  Google Scholar 

  41. Eckel WP, Kind T (2003) Use of boiling point-Lee retention index correlation for rapid review of gas chromatography-mass spectrometry data. Anal Chim Acta 494:235–243

    Article  CAS  Google Scholar 

  42. USEPA (2007) Estimation program interface (EPI) suite (TM) V3.20. United States Environmental Protection Agency, Washington DC

    Google Scholar 

  43. OECD (2004) Guideline for the testing of chemicals 117. Partition coefficient (n-octanol/water) – high performance liquid chromatography (HPLC) method

    Google Scholar 

  44. Paschke A, Manz M, Schuurmann G (2001) Application of different RP-HPLC methods for the determination of the octanol/water partition coefficient of selected tetrachlorobenzyltoluenes. Chemosphere 45:721–728

    Article  CAS  Google Scholar 

  45. Schulze T, Weiss S, Schymanski E, Von der Ohe PC, Schmitt-Jansen M, Altenburger R, Streck H-G, Brack W (2010) Confirmation of identity and phytotoxicity of a photo-transformation product of diclofenac. Environ Pollut 158:1461–1466

    Article  CAS  Google Scholar 

  46. ACD (2009) ACD/logD http://www.acdlabs.com/products/phys_chem_lab/logd/. Accessed: 02/02/2010. Advanced Chemistry Development, Inc

  47. Abraham MH, Roses M, Poole CF, Poole SK (1997) Hydrogen bonding.42. Characterization of reversed-phase high-performance liquid chromatographic C-18 stationary phases. J Phys Org Chem 10:358–368

    Article  CAS  Google Scholar 

  48. Schmitt-Jansen M, von der Ohe P, Franz S, Rotter S, Sabater S, de Zwart D, Segner H (2011) Ecological relevance of key toxicants in aquatic systems. In: Brack W (ed) Effect-directed analysis of complex environmental contamination. Springer, Heidelberg

    Google Scholar 

  49. Platts JA, Butina D, Abraham MH, Hersey A (1999) Estimation of molecular linear free energy relation descriptors using a group contribution approach. J Chem Inf Comput Sci 39:835–845

    CAS  Google Scholar 

  50. Schwobel J, Ebert RU, Kuhne R, Schuurmann G (2009) Modeling the H bond donor strength of -OH, -NH, and -CH sites by local molecular parameters. J Comput Chem 30:1454–1464

    Article  Google Scholar 

  51. Allinger NL (1977) Conformational-analysis.130. MM2 – hydrocarbon force-field utilizing V1 and V2 torsional terms. J Am Chem Soc 99:8127–8134

    Article  CAS  Google Scholar 

  52. CambridgeSoft (2007) ChemBio3D 11.0. CambridgeSoft

    Google Scholar 

  53. von der Ohe PC, Kuhne R, Ebert RU, Altenburger R, Liess M, Schuurmann G (2005) Structural alerts – a new classification model to discriminate excess toxicity from narcotic effect levels of organic compounds in the acute daphnid assay. Chem Res Toxicol 18:536–555

    Article  Google Scholar 

  54. Kazius J, McGuire R, Bursi R (2005) Derivation and validation of toxicophores for mutagenicity prediction. J Med Chem 48:312–320

    Article  CAS  Google Scholar 

  55. Skoczynska E, Korytar P, De Boer J (2008) Maximizing chromatographic information from environmental extracts by GCxGC-ToF-MS. Environ Sci Technol 42:6611–6618

    Article  CAS  Google Scholar 

  56. Hao HP, Cui N, Wang GJ, Xiang BR, Liang Y, Xu XY, Zhang H, Yang J, Zheng CN, Wu L, Gong P, Wang W (2008) Global detection and identification of nontarget components from herbal preparations by liquid chromatography hybrid ion trap time-of-flight mass spectrometry and a strategy. Anal Chem 80:8187–8194

    Article  CAS  Google Scholar 

  57. Meinert C, Schymanski E, Kuster E, Kuhne R, Schuurmann G, Brack W (2010) Application of preparative capillary gas chromatography (pcGC), automated structure generation and mutagenicity prediction to improve effect-directed analysis of genotoxicants in a contaminated groundwater. Environ Sci Pollut Res 17:885–897

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This chapter was supported by the European Commission through the Integrated Project MODELKEY (Contract No. 511237-GOCE). Our thanks go to Dr. M. Meringer, Prof. A. Kerber, and colleagues for on-going use and development of the MOLGEN series of programs, to C. Gallampois for the measurement data and to Dr. K. Thomas for reviewing the document.

Author information

Author notes

  1. Jos Hermans

    Present address: Department of Analytical Biochemistry, Centre of Pharmacy, University of Groningen, Antonius Deusinglaan 1, 9713 AV, Groningen, The Netherlands

Authors and Affiliations

  1. Department of Effect-Directed Analysis, UFZ Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318, Leipzig, Germany

    Emma Schymanski, Tobias Schulze & Werner Brack

  2. Public Works and Water Management, Ministry of Transport, Zuiderwagenplein 2, 8224 AD, Lelystad, The Netherlands

    Jos Hermans

Authors
  1. Emma Schymanski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tobias Schulze
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jos Hermans
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Werner Brack
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Emma Schymanski .

Editor information

Editors and Affiliations

  1. for Environmental Research, Department of Effect-Directed Analysis, UFZ Helmholtz Centre, Permoserstr. 15, Leipzig, 04318, Sachsen, Germany

    Werner Brack

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Schymanski, E., Schulze, T., Hermans, J., Brack, W. (2011). Computer Tools for Structure Elucidation in Effect-Directed Analysis. In: Brack, W. (eds) Effect-Directed Analysis of Complex Environmental Contamination. The Handbook of Environmental Chemistry(), vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18384-3_8

Download citation

Publish with us

Policies and ethics

Search

Navigation