Linked Life Data

20740553

Source:http://linkedlifedata.com/resource/pubmed/id/20740553

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
14
pubmed:dateCreated
2010-8-26
pubmed:abstractText
SKATE is a docking prototype that decouples systematic sampling from scoring. This novel approach removes any interdependence between sampling and scoring functions to achieve better sampling and, thus, improves docking accuracy. SKATE systematically samples a ligand's conformational, rotational and translational degrees of freedom, as constrained by a receptor pocket, to find sterically allowed poses. Efficient systematic sampling is achieved by pruning the combinatorial tree using aggregate assembly, discriminant analysis, adaptive sampling, radial sampling, and clustering. Because systematic sampling is decoupled from scoring, the poses generated by SKATE can be ranked by any published, or in-house, scoring function. To test the performance of SKATE, ligands from the Asetex/CDCC set, the Surflex set, and the Vertex set, a total of 266 complexes, were redocked to their respective receptors. The results show that SKATE was able to sample poses within 2 A RMSD of the native structure for 98, 95, and 98% of the cases in the Astex/CDCC, Surflex, and Vertex sets, respectively. Cross-docking accuracy of SKATE was also assessed by docking 10 ligands to thymidine kinase and 73 ligands to cyclin-dependent kinase.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1096-987X
pubmed:author
pubmed:copyrightInfo
2010 Wiley Periodicals, Inc.
pubmed:issnType
Electronic
pubmed:day
15
pubmed:volume
31
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2540-54
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
SKATE: a docking program that decouples systematic sampling from scoring.
pubmed:affiliation
Department of Biochemistry and Molecular Biophysics, Center for Computational Biology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, Missouri 63110, USA.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural