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LASSO-ing Potential Nuclear Receptor Agonists and Antagonists : A New Computational Method for Database Screening
Joint Authors
Goldsmith, Michael-Rock
Simon, Aniko
Ekins, Sean
Zsoldos, Zsolt
Ravitz, Orr
Williams, Antony J.
Source
Journal of Computational Medicine
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-06-24
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Nuclear receptors (NRs) are important biological macromolecular transcription factors that are implicated in multiple biological pathways and may interact with other xenobiotics that are endocrine disruptors present in the environment.
Examples of important NRs include the androgen receptor (AR), estrogen receptors (ER), and the pregnane X receptor (PXR).
In this study we have utilized the Ligand Activity by Surface Similarity Order (LASSO) method, a ligand-based virtual screening strategy to derive structural (surface/shape) molecular features used to generate predictive models of biomolecular activity for AR, ER, and PXR.
For PXR, twenty-five models were built using between 8 to 128 agonists and tested using 3000, 8000, and 24,000 drug-like decoys including PXR inactive compounds (N=228).
Preliminary studies with AR and ER using LASSO suggested the utility of this approach with 2-fold enrichment factors at 20%.
We found that models with 64–128 PXR actives provided enrichment factors of 10-fold (10% actives in the top 1% of compounds screened).
The LASSO models for AR and ER have been deployed and are freely available online, and they represent a ligand-based prediction method for putative NR activity of compounds in this database.
American Psychological Association (APA)
Ekins, Sean& Goldsmith, Michael-Rock& Simon, Aniko& Zsoldos, Zsolt& Ravitz, Orr& Williams, Antony J.. 2013. LASSO-ing Potential Nuclear Receptor Agonists and Antagonists : A New Computational Method for Database Screening. Journal of Computational Medicine،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-477612
Modern Language Association (MLA)
Ekins, Sean…[et al.]. LASSO-ing Potential Nuclear Receptor Agonists and Antagonists : A New Computational Method for Database Screening. Journal of Computational Medicine No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-477612
American Medical Association (AMA)
Ekins, Sean& Goldsmith, Michael-Rock& Simon, Aniko& Zsoldos, Zsolt& Ravitz, Orr& Williams, Antony J.. LASSO-ing Potential Nuclear Receptor Agonists and Antagonists : A New Computational Method for Database Screening. Journal of Computational Medicine. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-477612
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-477612