Document Detail


Lessons learned in empirical scoring with smina from the CSAR 2011 benchmarking exercise.
MedLine Citation:
PMID:  23379370     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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 data set, 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.
Authors:
David Ryan Koes; Matthew P Baumgartner; Carlos J Camacho
Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural     Date:  2013-02-12
Journal Detail:
Title:  Journal of chemical information and modeling     Volume:  53     ISSN:  1549-960X     ISO Abbreviation:  J Chem Inf Model     Publication Date:  2013 Aug 
Date Detail:
Created Date:  2013-08-26     Completed Date:  2014-03-21     Revised Date:  2014-08-27    
Medline Journal Info:
Nlm Unique ID:  101230060     Medline TA:  J Chem Inf Model     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1893-904     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Benchmarking
Databases, Pharmaceutical*
Drug Discovery / methods*
Molecular Docking Simulation
Protein Conformation
Structure-Activity Relationship
Grant Support
ID/Acronym/Agency:
R01 GM097082/GM/NIGMS NIH HHS; R01GM097082-01/GM/NIGMS NIH HHS
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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