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J Mol Graph Model. 2016 Mar;64:30-39. doi: 10.1016/j.jmgm.2015.12.006. Epub 2016 Jan 4.

Identification of estrogen receptor α ligands with virtual screening techniques.

Author information

1
Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014, Finland.
2
Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014, Finland; School of Pharmacy, Devi Ahilya University, Indore 452001, Madhya Pradesh, India.
3
Department of Chemistry & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014, Finland.
4
Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014, Finland. Electronic address: olli.t.pentikainen@jyu.fi.

Abstract

Utilization of computer-aided molecular discovery methods in virtual screening (VS) is a cost-effective approach to identify novel bioactive small molecules. Unfortunately, no universal VS strategy can guarantee high hit rates for all biological targets, but each target requires distinct, fine-tuned solutions. Here, we have studied in retrospective manner the effectiveness and usefulness of common pharmacophore hypothesis, molecular docking and negative image-based screening as potential VS tools for a widely applied drug discovery target, estrogen receptor α (ERα). The comparison of the methods helps to demonstrate the differences in their ability to identify active molecules. For example, structure-based methods identified an already known active ligand from the widely-used bechmarking decoy molecule set. Although prospective VS against one commercially available database with around 100,000 drug-like molecules did not retrieve many testworthy hits, one novel hit molecule with pIC50 value of 6.6, was identified. Furthermore, our small in-house compound collection of easy-to-synthesize molecules was virtually screened against ERα, yielding to five hit candidates, which were found to be active in vitro having pIC50 values from 5.5 to 6.5.

KEYWORDS:

3D-QSAR; Estrogen receptor alpha; Ligand discovery; Molecular docking; Negative image; Pharmacophore modeling; Virtual screening

PMID:
26774287
DOI:
10.1016/j.jmgm.2015.12.006
[Indexed for MEDLINE]

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