Literature DB >> 17918820

Target specific virtual screening: optimization of an estrogen receptor screening platform.

Andrew J S Knox1, Mary J Meegan, Vladimir Sobolev, Dermot Frost, Daniela M Zisterer, D Clive Williams, David G Lloyd.   

Abstract

In this work, we introduce a four-step scoring and filtering procedure, furnishing target specific virtual screening (TS-VS), which serves to minimize false positives resulting from conformational artifacts of the docking process and is optimized to converge on novel chemotypes of estrogen receptor alpha (ERalpha). As a proof of concept, VS of a commercial compound database was undertaken (SPECs database release: Aug 2005, 202 054 compounds in total), resulting in the identification of both previously known and novel putative ER scaffolds. Application of distance constraints within TS-VS allowed facile identification of three novel active ligands with ERalpha binding affinities (IC50) of 1.4 microM, 57 nM, and 53 nM. Importantly, they all exhibited ERalpha over ERbeta selectivity, with the most selective being 17-fold. The ligands also displayed low micomolar antiproliferative activity (7-15 microM) in the human MCF-7 breast cancer cell line.

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Year:  2007        PMID: 17918820     DOI: 10.1021/jm0700262

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  5 in total

1.  Crystal structure-based virtual screening for fragment-like ligands of the human histamine H(1) receptor.

Authors:  Chris de Graaf; Albert J Kooistra; Henry F Vischer; Vsevolod Katritch; Martien Kuijer; Mitsunori Shiroishi; So Iwata; Tatsuro Shimamura; Raymond C Stevens; Iwan J P de Esch; Rob Leurs
Journal:  J Med Chem       Date:  2011-11-07       Impact factor: 7.446

Review 2.  Statistical analysis, optimization, and prioritization of virtual screening parameters for zinc enzymes including the anthrax toxin lethal factor.

Authors:  Kimberly M Maize; Xia Zhang; Elizabeth Ambrose Amin
Journal:  Curr Top Med Chem       Date:  2014       Impact factor: 3.295

Review 3.  Understanding nuclear receptors using computational methods.

Authors:  Ni Ai; Matthew D Krasowski; William J Welsh; Sean Ekins
Journal:  Drug Discov Today       Date:  2009-03-11       Impact factor: 7.851

Review 4.  Computer-Aided Ligand Discovery for Estrogen Receptor Alpha.

Authors:  Divya Bafna; Fuqiang Ban; Paul S Rennie; Kriti Singh; Artem Cherkasov
Journal:  Int J Mol Sci       Date:  2020-06-12       Impact factor: 5.923

5.  Aurintricarboxylic acid inhibits influenza virus neuraminidase.

Authors:  Hui-Chen Hung; Ching-Ping Tseng; Jinn-Moon Yang; Yi-Wei Ju; Sung-Nain Tseng; Yen-Fu Chen; Yu-Sheng Chao; Hsing-Pang Hsieh; Shin-Ru Shih; John T-A Hsu
Journal:  Antiviral Res       Date:  2008-11-17       Impact factor: 5.970

  5 in total

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