Linked Life Data

10866370

Source:http://linkedlifedata.com/resource/pubmed/id/10866370

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2000-11-7
pubmed:abstractText
Monte Carlo statistical mechanics simulations have been carried out for 150 organic solutes in water. Physically significant descriptors such as the solvent-accessible surface area, numbers of hydrogen bonds, and indices for cohesive interactions in solids are correlated with pharmacologically important properties including octanol/water partition coefficient (log P) and aqueous solubility (log S). The regression equation for log S only requires five descriptors to provide a correlation coefficient, r2, of 0.9 and rms error of 0.7 for the 150 solutes. The descriptors can form a basis for structural modifications to guide an analogue's properties into desired ranges.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0960-894X
pubmed:author
pubmed:issnType
Print
pubmed:day
5
pubmed:volume
10
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1155-8
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Prediction of drug solubility from Monte Carlo simulations.
pubmed:affiliation
Department of Chemistry, Yale University, New Haven, CT 06520-8107, USA. bill@adrik.chem.yale.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.