Linked Life Data

11272702

Source:http://linkedlifedata.com/resource/pubmed/id/11272702

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2001-3-1
pubmed:abstractText
The optimizer developed for the Mining Minima algorithm, which uses ideas from Genetic Algorithms, the Global Underestimator Method, and Poling, has been adapted for use in ligand-receptor docking. The present study describes the resulting methodology and evaluates its accuracy and speed for 27 test systems. The performance of the new docking algorithm appears to be competitive with that of previously published methods. The energy model, an empirical force field with a distance-dependent dielectric treatment of solvation, is adequate for a number of test cases, although incorrect low-energy conformations begin to compete with the correct conformation for larger sampling volumes and for highly solvent-exposed binding sites that impose little steric constraint on the ligand.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0920-654X
pubmed:author
pubmed:issnType
Print
pubmed:volume
15
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
157-71
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Ligand-receptor docking with the Mining Minima optimizer.
pubmed:affiliation
Center for Advanced Research in Biotechnology, Rockville, MD 20850, USA.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S.