Linked Life Data

16426061

Source:http://linkedlifedata.com/resource/pubmed/id/16426061

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2006-1-23
pubmed:abstractText
A recently introduced new methodology based on ultrashort (50-100 ps) molecular dynamics simulations with a quantum-refined force-field (QRFF-MD) is here evaluated in its ability both to predict protein-ligand binding affinities and to discriminate active compounds from inactive ones. Physically based scoring functions are derived from this approach, and their performance is compared to that of several standard knowledge-based scoring functions. About 40 inhibitors of cyclin-dependent kinase 2 (CDK2) representing a broad chemical diversity were considered. The QRFF-MD method achieves a correlation coefficient, R(2), of 0.55, which is significantly better than that obtained by a number of traditional approaches in virtual screening but only slightly better than that obtained by consensus scoring (R(2) = 0.50). Compounds from the Available Chemical Directory, along with the known active compounds, were docked into the ATP binding site of CDK2 using the program Glide, and the 650 ligands from the top scored poses were considered for a QRFF-MD analysis. Combined with structural information extracted from the simulations, the QRFF-MD methodology results in similar enrichment of known actives compared to consensus scoring. Moreover, a new scoring function is introduced that combines a QRFF-MD based scoring function with consensus scoring, which results in substantial improvement on the enrichment profile.
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
254-63
pubmed:dateRevised
2009-11-19
pubmed:meshHeading
pubmed:articleTitle
New scoring functions for virtual screening from molecular dynamics simulations with a quantum-refined force-field (QRFF-MD). Application to cyclin-dependent kinase 2.
pubmed:affiliation
Novartis Institutes for BioMedical Research, Discovery Technologies, Basel, Switzerland. phillipe.ferrara@novartis.com
pubmed:publicationType
Journal Article