Abstract
We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by molecular docking of more than 1000 chemicals into 150 protein targets and contains nearly 135 thousand unique ligand/target binding scores. Obtaining this dataset was achieved using eHiTS (Simbiosys Inc.), a fragment-based molecular docking approach with an exhaustive search algorithm, on a heterogeneous distributed high-performance computing framework. The chemical landscape covered in DockScreen comprises selected environmental and therapeutic chemicals. The target landscape covered in DockScreen was selected based on the availability of high-quality crystal structures that covered the assay space of phase I ToxCast in vitro assays. This in silico data provides continuous information that establishes a means for quantitatively comparing, on a structural biophysical basis, a chemical’s profile of biomolecular interactions. The combined minimum-score chemical/target matrix is provided.
Highlights
A major challenge with chemicals in consumer products, including but not limited to both pharmaceutical and environmental chemicals, is the ability to fully discover, characterize, and anticipate adverse effects that may result as a consequence of exposure to these chemicals
In an attempt to fill the inherently large data gaps required for modern risk assessment [6] and to develop both time- and cost-effective approaches for prioritizing the toxicity testing of large numbers of chemicals, the ToxCast program was initiated [7]
The unparalleled amount of data, low cost, high speed, and rich information content afforded by in silico structure-based inquiry in addition to the large number of public resources for both target crystal structures and chemical libraries has urged us to consider the development of a structure-based in silico database, DockScreen, to complement both the ToxCast program’s screening/prioritization effort and computational toxicology in general
Summary
A major challenge with chemicals in consumer products, including but not limited to both pharmaceutical and environmental chemicals, is the ability to fully discover, characterize, and anticipate adverse effects that may result as a consequence of exposure to these chemicals. Developing and evaluating predictive strategies to elucidate the mode of biological activity of environmental chemicals are major undertaking of the US Environmental Protection Agency’s Computational Toxicology program (http:// www.epa.gov/comptox/) Aligning these strategies with the Agency’s ongoing chemical-specific risk assessment needs provision of additional incentive to develop new means of elucidating key determinants of toxicity in the chemical source-to-outcome continuum at a molecular level of accountability. The unparalleled amount of data, low cost, high speed, and rich information content (i.e., high content data) afforded by in silico structure-based inquiry (e.g., molecular docking) in addition to the large number of public resources for both target crystal structures and chemical libraries has urged us to consider the development of a structure-based in silico database, DockScreen, to complement both the ToxCast program’s screening/prioritization effort and computational toxicology in general. We have created a web interface for accessing the data including multiple binding poses and scores for each protein/ ligand pairing, but this report is limited to only the most generally useful data: a table containing the highest score obtained for the docking of each ligand to each crystal structure
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