A high-throughput, computational system to predict if environmental contaminants can bind to human nuclear receptors

Xiaoxiang Wang, Xiaowei Zhang, Pu Xia, Junjiang Zhang, Yuting Wang, Rui Zhang, John P. Giesy, Wei Shi*, Hongxia Yu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Some pollutants can bind to nuclear receptors (NRs) and modulate their activities. Predicting interactions of NRs with chemicals is required by various jurisdictions because these molecular initiating events can result in adverse, apical outcomes, such as survival, growth or reproduction. The goal of this study was to develop a high-throughput, computational method to predict potential agonists of NRs, especially for contaminants in the environment or to which people or wildlife are expected to be exposed, including both persistent and pseudo-persistent chemicals. A 3D-structure database containing 39 human NRs was developed. The database was then combined with AutoDock Vina to develop a System for Predicting Potential Effective Nuclear Receptors (SPEN), based on inverse docking of chemicals. The SPEN was further validated and evaluated by experimental results for a subset of 10 chemicals. Finally, to assess the robustness of SPEN, its ability to predict potentials of 40 chemicals to bind to some of the most studied receptors was evaluated. SPEN is rapid, cost effective and powerful for predicting binding of chemicals to NRs. SPEN was determined to be useful for screening chemicals so that pollutants in the environment can be prioritized for regulators or when considering alternative compounds to replace known or suspected contaminants with poor environmental profiles.

Original languageEnglish
Pages (from-to)609-616
Number of pages8
JournalScience of the Total Environment
Volume576
DOIs
Publication statusPublished - 15 Jan 2017

Bibliographical note

Funding Information:
This work was supported by Natural Science Foundation of China ( 21577058 & 21307054 ), Non-profit Industry Research Subject ( 201409040 ), Natural Science Foundation of Jiangsu Province ( BK20130551 ), Major Science and Technology Program for Water Pollution Control and Treatment ( 2012ZX07101-003 ), Specialized Research Fund for the Doctoral Program of Higher Education ( 20130091120013 ), and the Collaborative Innovation Center for Regional Environmental Quality. The computational calculations were performed on the IBM Blade cluster system in the High Performance Computing Center (HPCC) of Nanjing University. Prof. Giesy was supported by the “High Level Foreign Experts” program (#GDT20143200016) funded by the State Administration of Foreign Experts Affairs, the P.R. China to Nanjing University and the Einstein Professor Program of the Chinese Academy of Sciences. He was also supported by the Canada Research Chair program and a Distinguished Visiting Professorship in the School of Biological Sciences of the University of Hong Kong. We thank the anonymous reviewers for their careful reading of our manuscript and their many insightful comments and suggestions.

Publisher Copyright:
© 2016

Keywords

  • Agonists
  • Endocrine disrupting activities
  • Inverse docking
  • Nuclear receptors

ASJC Scopus subject areas

  • Environmental Engineering
  • Environmental Chemistry
  • Waste Management and Disposal
  • Pollution

Fingerprint

Dive into the research topics of 'A high-throughput, computational system to predict if environmental contaminants can bind to human nuclear receptors'. Together they form a unique fingerprint.

Cite this