Computational Toxicology

Chapter 8Computational Tools for ADMET Profiling

Denis Fourches¹, Antony J. Williams², Grace Patlewicz², Imran Shah², Chris Grulke², John Wambaugh², Ann Richard² and Alexander Tropsha³

¹Department of Chemistry, Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA

²National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, USA

³UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Chapter Menu

1. Introduction
2. Cheminformatics Approaches for ADMET Profiling
3. Unsolved Challenges in Structure Based Profiling
4. Perspectives
5. Conclusions
6. Disclaimer

8.1 Introduction

Large quantities of ADMET-related chemical biological data have been released in the public domain in the past decade [1, 2]. This growth was mainly due to (i) large federally sponsored high-throughput screening (HTS) programs (e.g., Tox21, ToxCast) [3–6] with on-going efforts to test thousands of chemicals against hundreds of relevant short-term assays; (ii) development of online repositories (e.g., ChEMBL, PubChem) [7, 8] that actively collected, integrated, and stored chemogenomics data extracted from literature and/or directly deposited by researchers; and (iii) contributions from pharmaceutical companies that publicly released enormous amounts of internal screening data not considered to be strategic anymore (e.g., GSK PKIS and antimalarial sets) [9, ...