This article is part of the supplement: 4th German Conference on Chemoinformatics: 22. CIC-Workshop .

Poster presentation

Components for computer-assisted structure elucidation

S Kuhn, G Torrance and C Steinbeck

Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK

corresponding author email

from 4th German Conference on Chemoinformatics
Goslar, Germany. 9–11 November 2008

Chemistry Central Journal 2009, 3(Suppl 1):P62doi:10.1186/1752-153X-3-S1-P62

The electronic version of this abstract is the complete one and can be found online at: http://www.journal.chemistrycentral.com/content/3/S1/P62

Published:

5 June 2009

© 2009 Kuhn et al; licensee BioMed Central Ltd.

Poster presentation

Computer-Assisted Structure Elucidation (CASE) is of relevance for various fields in chemistry and biology such as natural products discovery or metabolomics. Here we report on several software components developed in our team over time which can form part of an integrated CASE package. We aim to design a user-friendly and flexible, yet powerful tool with Bioclipse [1] as the frontend. Bioclipse is an integrated software suite for chemo- and bioinformatics providing plug-ins for file handling and visualisation of compounds and spectra. Spectrum look-up and prediction is provided by our open NMR database NMRShiftDB [2], offering both 13C and 1H NMR prediction. We have recently demonstrated the prediction of proton NMR spectra based on NMRShiftDB data with an average error of 0.18 ppm [3]. The resulting CASE system will provide a choice of different structure generators, including stochastic search engines, based on Simulated Annealing and Genetic Algorithms.

References

1. Spjuth O, Helmus T, Willighagen EL, Kuhn S, Eklund M, et al.: Bioclipse: An open source workbench for chemo- and bioinformatics.

   BMC Bioinformatics 2007 , 8:59. PubMed Abstract | BioMed Central Full Text | PubMed Central Full Text

2. Steinbeck C, Krause S, Kuhn S: NMRShiftDB – Constructing a free chemical information system with open-source components.

   J Chem Inf Comp Sci 2003 , 43:1733-1739.

3. Kuhn S, Egert B, Neumann S, Steinbeck C: Building blocks for automated elucidation of metabolites: Machine learning methods for NMR prediction.

   BMC Bioinformatics 2008 , 9:400. PubMed Abstract | BioMed Central Full Text | PubMed Central Full Text

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