Linked Life Data

16426072

Source:http://linkedlifedata.com/resource/pubmed/id/16426072

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2006-1-23
pubmed:abstractText
Here, the comparisons of performance of nine consensus scoring strategies, in which multiple scoring functions were used simultaneously to evaluate candidate structures for a protein-ligand complex, in combination with nine scoring functions (FlexX score, GOLD score, PMF score, DOCK score, ChemScore, DrugScore, PLP, ScreenScore, and X-Score), were carried out. The systematic naming of consensus scoring strategies was also proposed. Our results demonstrate that choosing the most appropriate type of consensus score is essential for model selection in computational docking; although the vote-by-number strategy was an effective selection method, the number-by-number and rank-by-number strategies were more appropriate when computational tractability was taken into account. By incorporating these consensus scores into the FlexX program, reasonable complex models can be obtained more efficiently than those selected by independent FlexX scores. These strategies might also improve the scoring of other docking programs, and more-effective structure-based drug design should result from these improvements.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1549-9596
pubmed:author
pubmed:issnType
Print
pubmed:volume
46
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
380-91
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:articleTitle
Comparison of consensus scoring strategies for evaluating computational models of protein-ligand complexes.
pubmed:affiliation
Discovery Laboratories, Toyama Chemical Co., Ltd., Japan. AKIFUMI_ODA@toyama-chemical.co.jp
pubmed:publicationType
Journal Article, Comparative Study