Linked Life Data

20488738

Source:http://linkedlifedata.com/resource/pubmed/id/20488738

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2010-8-17
pubmed:abstractText
Natural products (NPs) have been widely used in traditional medicines and are a valuable source for new drug discovery. However, insufficient knowledge about their molecular mechanisms has limited the scope of their application and hindered the effort to design new drugs from their synergistic action strategies. Thus far, a systematic study of all NP ingredients in a traditional medicine recipe remains impractical. However encouraging results have begun to appear illustrating synergies between several principle active ingredients. In this work, we propose the use of structure activity relationship (SAR) to identify potential active ingredients in natural products, with the aim to facilitate experimental and computational characterizations of their therapeutic mechanisms and synergies. We call this approach the bioactive natural compound-likeness (BNC-likeness) approach, drawing a parallel to the concept of drug-likeness. In cross-validations and independent example tests, our approach displayed 90-92% sensitivity and 85-90% specificity, suggesting its practical usefulness. We also showed that BNC-like compounds were not just drug-like NP ingredients. BNC-like compounds and drug-like chemicals may share different structural characteristics. Therefore, BNC-likeness is a helpful novel conception inviting dedicated research.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
1873-4243
pubmed:author
pubmed:issnType
Electronic
pubmed:day
24
pubmed:volume
29
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
38-45
pubmed:dateRevised
2011-11-17
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Computational identification of bioactive natural products by structure activity relationship.
pubmed:affiliation
Department of Bioinformatics, Zhejiang University, Hangzhou, PR China.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't