| Integrating Medicinal Chemistry, Organic/Combinatorial Chemistry and Computational Chemistry for the Discovery of Selective Estrogen Receptor Modulators with FORECASTER, a Novel Platform for Drug Discovery. | |
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MedLine Citation:
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PMID: 22133077 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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As part of a large medicinal chemistry program, we wish to develop novel selective estrogen receptor modulators (SERMs) as potential breast cancer treatments using a combination of experimental and computational approaches. However, one of the remaining difficulties nowadays is to fully integrate computational (i.e., virtual, theoretical) and medicinal (i.e., experimental, intuitive) chemistry to take advantage of the full potential of both. For this purpose, we have developed a web-based platform, FORECASTER, and a number of programs (e.g., PREPARE, REACT, SELECT) with the aim of combining computational chemistry and medicinal chemistry expertises to facilitate drug discovery and development and more specifically to integrate synthesis into computer-aided drug design. In our quest for potent SERMs, this platform was used to build virtual combinatorial libraries, filter and extract a highly diverse library from the NCI database and dock them to the estrogen receptor (ER), with all these steps being fully automated by computational chemists for use by medicinal chemists. As a result, virtual screening of a diverse library seeded with active compounds followed by a search for analogs yielded an enrichment factor of 129, with 98% of the seeded active compounds recovered, while the screening of a designed virtual combinatorial library including known actives yielded an area under the receiver operating characteristic (AU-ROC) of 0.78. The lead optimization proved less successful, further demonstrating the challenge to simulate structure activity relationship studies. |
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Authors:
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Eric Therrien; Pablo Englebienne; Andrew G Arrowsmith; Rodrigo Mendoza-Sanchez; Christopher Corbeil; Nathanael Weill; Valerie Campagna-Slater; Nicolas Moitessier |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-12-1 |
Journal Detail:
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Title: Journal of chemical information and modeling Volume: - ISSN: 1549-960X ISO Abbreviation: - Publication Date: 2011 Dec |
Date Detail:
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Created Date: 2011-12-2 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101230060 Medline TA: J Chem Inf Model Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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