Linked Life Data

11718475

Source:http://linkedlifedata.com/resource/pubmed/id/11718475

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
2001-11-22
pubmed:abstractText
The brain-blood partition coefficient (log BB) is a determining factor for the efficacy of central nervous system acting drugs. Since large-scale experimental determination of log BB is unfeasible, alternative evaluation methods based on theoretical models are desirable. Toward this direction, we propose a model that correlates log BB with physically significant descriptors for 76 structurally diverse molecules. We employ Monte Carlo simulations of the compounds in water to calculate such properties as the solvent-accessible surface area (SASA), the number of hydrogen bond donors and acceptors, the solute dipole, and the hydrophilic, hydrophobic and amphiphilic components of SASA. The physically significant descriptors are identified and a quantitative structure-prediction relationship is constructed that predicts log BB. This work demonstrates that computer simulations can be employed in a semi-empirical framework to build predictive QSPRs that shed light on the physical mechanism of biomolecular phenomena.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0920-654X
pubmed:author
pubmed:issnType
Print
pubmed:volume
15
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
697-708
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Prediction of blood-brain partitioning using Monte Carlo simulations of molecules in water.
pubmed:affiliation
Department of Chemical Engineering, University of Michigan, Ann Arbor 48109, USA. yiannis@cems.umn.edu
pubmed:publicationType
Journal Article, In Vitro, Research Support, Non-U.S. Gov't