In Silico Prediction of Endocrine Disrupting Chemicals Using Single-Label and Multilabel Models

2019 ◽  
Vol 59 (3) ◽  
pp. 973-982 ◽  
Author(s):  
Lixia Sun ◽  
Hongbin Yang ◽  
Yingchun Cai ◽  
Weihua Li ◽  
Guixia Liu ◽  
...  
Keyword(s):  
In Silico ◽  
Endocrine Disrupting Chemicals ◽  
In Silico Prediction ◽  
Endocrine Disrupting

scholarly journals In Silico Molecular Docking and In Vivo Validation with Caenorhabditis elegans to Discover Molecular Initiating Events in Adverse Outcome Pathway Framework: Case Study on Endocrine-Disrupting Chemicals with Estrogen and Androgen Receptors

2019 ◽  
Vol 20 (5) ◽  
pp. 1209 ◽  
Author(s):  
Jaeseong Jeong ◽  
Hunbeen Kim ◽  
Jinhee Choi
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Adverse Outcome ◽  
Endocrine Disrupting Chemicals ◽  
Reproductive Toxicity ◽  
Adverse Outcome Pathway ◽  
C Elegans ◽  
Endocrine Disrupting ◽  
Mutant Strains

Molecular docking is used to analyze structural complexes of a target with its ligand for understanding the chemical and structural basis of target specificity. This method has the potential to be applied for discovering molecular initiating events (MIEs) in the Adverse Outcome Pathway framework. In this study, we aimed to develop in silico–in vivo combined approach as a tool for identifying potential MIEs. We used environmental chemicals from Tox21 database to identify potential endocrine-disrupting chemicals (EDCs) through molecular docking simulation, using estrogen receptor (ER), androgen receptor (AR) and their homology models in the nematode Caenorhabditis elegans (NHR-14 and NHR-69, respectively). In vivo validation was conducted on the selected EDCs with C. elegans reproductive toxicity assay using wildtype N2, nhr-14, and nhr-69 loss-of-function mutant strains. The chemicals showed high binding affinity to tested receptors and showed the high in vivo reproductive toxicity, and this was further confirmed using the mutant strains. The present study demonstrates that the binding affinity from the molecular docking potentially correlates with in vivo toxicity. These results prove that our in silico–in vivo combined approach has the potential to be applied for identifying MIEs. This study also suggests the potential of C. elegans as useful in the in vivo model for validating the in silico approach.

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