Table of Contents
Dataset Papers in Science
Volume 2014 (2014), Article ID 421693, 5 pages
http://dx.doi.org/10.1155/2014/421693
Dataset Paper

DockScreen: A Database of In Silico Biomolecular Interactions to Support Computational Toxicology

1Chemical Computing Group, 1010 Sherbrooke Street W., Suite 910, Montreal, QC, Canada H3A 2R7
2Lockheed Martin Information Technology, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA
3Office of Research & Development, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA

Received 6 June 2014; Accepted 16 September 2014; Published 11 November 2014

Academic Editor: Josefina Pons

Copyright © 2014 Michael-Rock Goldsmith et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.