کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
442861 692413 2016 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Identification of estrogen receptor α ligands with virtual screening techniques
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی تئوریک و عملی
پیش نمایش صفحه اول مقاله
Identification of estrogen receptor α ligands with virtual screening techniques
چکیده انگلیسی


• Validation of commonly used virtual screening methods demonstrates differences in their ability to identify active molecules.
• Known active ligand was identified from the widely-used benchmarking decoy molecule set.
• Virtual screening based discovery identified several estrogen receptor alpha ligands.

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.

Figure optionsDownload high-quality image (190 K)Download as PowerPoint slide

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Molecular Graphics and Modelling - Volume 64, March 2016, Pages 30–39
نویسندگان
, , , , ,