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DSSTOX WEBSITE LAUNCH: IMPROVING PUBLIC ACCESS TO DATABASES FOR BUILDING STRUCTURE-TOXICITY PREDICTION MODELS
Citation:
Richard, A M. DSSTOX WEBSITE LAUNCH: IMPROVING PUBLIC ACCESS TO DATABASES FOR BUILDING STRUCTURE-TOXICITY PREDICTION MODELS. PRECLINICA 2(2):103-108, (2004).
Description:
DSSTox Website Launch: Improving Public Access to Databases for Building Structure-Toxicity Prediction Models
Ann M. Richard
US Environmental Protection Agency, Research Triangle Park, NC, USA
Distributed: Decentralized set of standardized, field-delimited databases, each separately
authored and maintained, that are able to accommodate diverse toxicity data content;
Structure-Searchable: Standard format (SDF) structure-data files that can be readily imported into available chemical relational databases and structure-searched;
Tox: Toxicity data as it exists in widely disparate forms in current public databases, spanning diverse toxicity endpoints, test systems, levels of biological content, degrees of summarization, and information content.
INTRODUCTION
The economic and social pressures to reduce the need for animal testing and to better anticipate the potential for human and eco-toxicity of environmental, industrial, or pharmaceutical chemicals are as pressing today as at any time prior. However, the goal of predicting chemical toxicity in its many manifestations, the `T' in 'ADMET' (adsorption, distribution, metabolism, elimination, toxicity), remains one of the most difficult and largely unmet challenges in a chemical screening paradigm [1]. It is widely acknowledged that the single greatest hurdle to improving structure-activity relationship (SAR) toxicity prediction capabilities, in both the pharmaceutical and environmental regulation arenas, is the lack of sufficient high quality data, for sufficient diversity of chemical structures, for the many and varied toxicity endpoints of potential concern. That toxicity endpoints can range from gross phenomenological disease measures (e.g., cancer, developmental malformations, hepatotoxicity), to hormone disruptions caused by highly specific receptor interactions (e.g., androgen or estrogen receptor binding), and can be metabolism-dependent and species/sex/tissue-specific, add further layers of complexity and challenge to this problem [2]. With the added recognition that toxicity data, particularly from whole animal studies, are a diminishing resource that will not likely be expanded significantly in the future, it is paramount to be able to fully mine the chemical toxicity data that currently exists [3].
There are two general informatics trends in biology that have facilitated explosive advances in genomics and structural biology, as well as many other areas of study: 1) data standardization and 2) on-line, open-access to well-documented data. Data standardization enables the collation of large amounts of data from disparate sources into a usable form for searching across standardized metrics. On-line, open access to data brings broad and varied intellectual capabilities to bear on data analysis, providing the fuel to feed the engine of scientific advancement. Two examples that bear out this assertion are the PDB (Protein Data Bank), a widely used public repository of crystallographic structure data [4], and the NCBI (National Center for Biotechnology Information), a treasure trove of on-line databases and bioinformatics data mining tools for exploring public genomics information. From an informatics standpoint, however, historical toxicity data present some difficult and unique challenges that have confounded efforts to create a centralized public data repository. Not only do these data exist in many formats and locations in the public domain, but they also span many levels of biological organization, detail, degrees of summarization and annotation, and disciplines of toxicological study [5,6]. The only common thread and shared information metric that truly has the potential to span and unify these disparate data is the molecular structure of the test chemical, and the underlying chemistry that it represents.