Data Exchange in Chemistry Figure 1. Metabolites found in oryza sativa plant organs. The flavor of basmati rice comes from 2-acetyl-1-pyrrolidine, beta-carotene enriched golden rice was created to defeat vitamin-A deficiencies in the third world and the compound Bisbynin is not created by rice itself but a parasitic soil fungus Stachybotrys bisbyi found in rice seeds. doi:10.1371/journal.pone.0005440.g001 such as mass spectrometry (MS) and nuclear magnetic resonance (NMR). Spectral information and other experimental physico- chemical descriptors need to be collected and disseminated for each single compound. We recently introduced approaches to use target molecule databases [3] for metabolic profiling purposes and annotation of unknown compounds [4]. To perform such annotations the correct molecular structure and if possible mass spectra must be obtained from database queries. From the molecular structure the accurate masses and isotopic abundances can be used and searched in experimental data sets. Additionally substance data can be matched against in-silico generated tandem mass spectra [5] or can be used in approaches using substructure detection algorithms and molecular isomer generators [6]. In order to limit the search space of compounds, such database approaches would benefit if information was given in which organisms (coded as taxonomy source) and in which organs or cell types these metabolites were known to exist. We here present results of a query of several databases combining all three approaches to metabolome compilation Figure 2. The process of building pathway and metabolite databases includes a) data extraction from the literature b) use of in-silico and ortholog mapping approaches and c) direct input from experimental databases like SetupX. Molecular pathway databases can be built for all known taxonomic species which can be found in the NCBI taxonomy database. doi:10.1371/journal.pone.0005440.g002 (literature, in-silico pathways and experimental data), using oryza sativa as example. We explain the difficulties in this process and discuss solutions to overcome the current procrastination and stagnation of data exchange practices in chemistry. Methods Searches were performed in October 2008. Results may not always reflect database updates that were released after this date. Due to the complexity of steps in cleaning and curating result data sets, actual numbers may differ to some degree if queries are repeated, while the overall conclusion on limitations with current database designs will be found reproducible. The CAS Chemical Abstracts Database [7] search was performed with SciFinder 2006 and 2007 version for Windows. Chemical Abstracts covers most of the chemical and patent literature since 1907. Annual institutional subscription is required for this database. Results were exported as CAS numbers and text. Analysis of substances count was performed within SciFinder. Search term was ‘oryza sativa’. To further constrain the search, ‘liquid chromatography’, ‘gas chromatography’, and ‘mass spectrometry’ were used as combined search terms using the intelligent query language (‘‘Oryza sativa and GC-MS’’ not pesticides’’). Histograms and categorizations and patent searches were performed with SciFinder. The CRC Press Dictionary of Natural Products search was performed using the web frontend (DNP 17.1 Copyright 2008 Taylor & Francis Group) [8]. Annual institutional subscription is required for this database. Search terms for biological source: ‘oryzae’ and ‘oryza sativa’. The PubChem database was searched with the terms ‘oryza sativa’ in the compound and substance section. Furthermore it was accessed via the National Center for Biotechnology Information (NCBI) Entrez search portal [9]. As the direct search resulted in zero hits (no taxonomy data is stored in PubChem) the search was performed via PubMed and PubMed Central [10]. PubMed Central was searched either with the term ‘oryza sativa’ or the taxonomy ID ‘txid4530’ [Organism:exp]. Substances in PubChem were shown with the display substance option in PubMed. The Beilstein database (Elsevier Information Systems GmbH) [11] was searched with the MDL CrossFire Commander 7.0 frontend. Annual institutional subscription is required for this database. The search term ‘oryza sativa’ was used. PLoS ONE | www.plosone.org 2 May 2009 | Volume 4 | Issue 5 | e5440