Linked Life Data

12825792

Source:http://linkedlifedata.com/resource/pubmed/id/12825792

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2003-6-26
pubmed:abstractText
The development of a scoring scheme for the classification of molecules into serine protease (SP) actives and inactives is described. The method employed a set of pre-selected descriptors for encoding the molecular structures, and a trained neural network for classifying the molecules. The molecular requirements were profiled and validated by using available databases of SP- and non-SP-active agents [1,439 diverse SP-active molecules, and 5,131 diverse non-SP-active molecules from the Ensemble Database (Prous Science, 2002)] and Sensitivity Analysis. The method enables an efficient qualification or disqualification of a molecule as a potential serine protease ligand. It represents a useful tool for constraining the size of virtual libraries that will help accelerate the development of new serine protease active drugs.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0920-654X
pubmed:author
pubmed:issnType
Print
pubmed:volume
16
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
803-7
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Classification scheme for the design of serine protease targeted compound libraries.
pubmed:affiliation
Chemical Diversity Labs, Inc., 11558 Sorrento Valley Road, San Diego, CA 92121, USA. slang@chemdiv.com
pubmed:publicationType
Journal Article