Linked Life Data

18038162

Source:http://linkedlifedata.com/resource/pubmed/id/18038162

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2007-12-6
pubmed:abstractText
Steric molecular field can be represented in a number of ways in comparative molecular field analysis (CoMFA). This study aimed to investigate whether the choice of steric molecular field settings significantly influences the predictive performance of CoMFA and, if so, which is the best. The three-dimensional quantitative structure activity relationship (3D-QSAR) models based on Lennard-Jones, indicator, parabolic and Gaussian steric fields were compared using 28 datasets taken from the literature. The analysis of the predictive ability of these models (cross validated R(2)) indicates that steric fields in which the value drops off quickly with distance (i.e. Lennard-Jones and indicator fields) tend to perform better than the Gaussian version, which has a slower and smoother decrease. Furthermore, depending on the steric field type used, the field sampling density (i.e. grid spacing) has a variable influence on the predictive ability of the models generated.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
0948-5023
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
14
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
59-67
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Effect of steric molecular field settings on CoMFA predictivity.
pubmed:affiliation
Sansom Institute, School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, SA 5000, Australia.
pubmed:publicationType
Journal Article