Linked Life Data

20726600

Source:http://linkedlifedata.com/resource/pubmed/id/20726600

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
2010-8-23
pubmed:abstractText
A database of about 700 high-resolution kinase structures was used to test the reliability of 17 docking procedures (using six docking software packages) by means of self- and cross-docking studies. The analysis of about 80 000 docking calculations suggests that the docking of an unknown ligand into a kinase has a probability of only 30-37% to be a correct ligand pose. However, based on the hypothesis that docking calculations are more reliable if the ligand to be docked is similar to the ligand present in the complex from which the target docking protein has been extracted, we propose an automated procedure that is able to improve the docking accuracy, suggest the best protein for docking studies, and assess the statistical reliability of docking calculations. The results were also transferred to the homology modeling field and led us to propose an alternative strategy based on ligand similarity for the development of kinase models whose experimental structure was not known. Our results suggest that in many cases this approach can give better results than the classical homology modeling procedure based exclusively on the sequence homology.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
1549-960X
pubmed:author
pubmed:issnType
Electronic
pubmed:day
23
pubmed:volume
50
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1432-41
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Protein kinases: docking and homology modeling reliability.
pubmed:affiliation
Dipartimento di Scienze Farmaceutiche, Universita di Pisa, via Bonanno 6, 56126 Pisa, Italy.
pubmed:publicationType
Journal Article