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Advances in Toxico-Cheminformatics: Supporting a New Paradigm for Predictive Toxicology
Citation:
RICHARD, A. M., M. Wolf, T. Transue, AND C. Williams-Devane. Advances in Toxico-Cheminformatics: Supporting a New Paradigm for Predictive Toxicology. Presented at European Symposium on Quantitative Structure-Activity Relationships and Omics Technologies and Systems Biology, Uppsala, SWEDEN, September 21 - 26, 2008.
Impact/Purpose:
The public DSSTox chemical and bioassay inventory has been recently integrated into PubChem, allowing a user to take full advantage of PubChem structure-activity and bioassay clustering features. The DSSTox project is providing cheminformatics support for EPA’s ToxCastTM project, as well as supporting collaborations with the National Toxicology Program (NTP) HTS and the NIH Chemical Genomics Center (NCGC). Phase I of the ToxCastTM project is generating HTS data from several hundred biochemical and cell-based assays for a set of 320 chemicals, mostly pesticide actives with rich toxicology profiles. Reference in vivo toxicity data for these compounds have been incorporated into a toxicity relational database, ToxRef DB, and the newly developed ACToR system will house all the data being collected and generated, as well as provide informatics and analysis support for ToxCastTM. Public data release of HTS, genomics, and reference toxicity data, through ACToR, DSSTox, and PubChem, is a central precept of the ToxCastTM effort. Incorporating structure-based data-mining capabilities and traditional SAR concepts into this new data-rich world poses conceptual and practical challenges, but holds great promise for improving predictive toxicology capabilities.
Description:
EPA’s National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction through the harnessing of legacy toxicity data, creation of data linkages, and generation of new high-throughput screening (HTS) data. The DSSTox project is working to improve public access to quality structure-annotated chemical toxicity information in less summarized forms than traditionally employed in SAR modeling, and in ways that facilitate both data-mining and read-across. Both DSSTox Structure-Files and the dedicated on-line DSSTox Structure-Browser are enabling seamless structure-based searching and linkages to and from previously isolated, chemically indexed public toxicity data resources (e.g., NTP, EPA IRIS, CPDB). Most recently, structure-enabled search capabilities have been extended to chemical exposure-related microarray experiments in the public EBI Array Express database, additionally linking this resource to the NIEHS CEBS toxicogenomics database.
URLs/Downloads:
Advances in Toxico-Cheminformatics: Supporting a New Paradigm for Predictive Toxicology (PDF, NA pp, 12 KB, about PDF)Advances in Toxico-Cheminformatics: Supporting a New Paradigm for Predictive Toxicology (slide) (PDF, NA pp, 6185 KB, about PDF)