| Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise. | |
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MedLine Citation:
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PMID: 23379370 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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We describe a general methodology for designing an empirical scoring function and provide smina, a version of AutoDock Vina specially optimized to support high-throughput scoring and user-specified custom scoring functions. Using our general method, the unique capabilities of \smina , a set of default interaction terms from AutoDock Vina, and the CSAR (Community Structure-Activity Resource) 2010 dataset, we created a custom scoring function and evaluated it in the context of the CSAR 2011 benchmarking exercise. We find that our custom scoring function does a better job sampling low RMSD poses when crossdocking compared to the default AutoDock Vina scoring function. The design and application of our method and scoring function reveal several insights into possible improvements and the remaining challenges when scoring and ranking putative ligands. |
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Authors:
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David Ryan Koes; Matthew P Baumgartner; Carlos J Camacho |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2013-2-4 |
Journal Detail:
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Title: Journal of chemical information and modeling Volume: - ISSN: 1549-960X ISO Abbreviation: J Chem Inf Model Publication Date: 2013 Feb |
Date Detail:
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Created Date: 2013-2-5 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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Descriptor/Qualifier:
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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