Linked Life Data

18466274

Source:http://linkedlifedata.com/resource/pubmed/id/18466274

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2008-5-20
pubmed:abstractText
Fingerprints are bit string representations of molecular structure and properties and widely used tools to search databases for active molecules. It is well appreciated that molecular complexity and size effects lead to systematic errors in fingerprint similarity searching. For example, different studies have highlighted the caveats associated with preferential recognition of large compounds, irrespective of their activity, when complex molecules are used as templates for fingerprint calculations. In order to systematically study complexity relationships between reference and database molecules that are relevant for practical fingerprint similarity searching, we have designed sets of active molecules of increasing fingerprint bit density relative to average database compounds and potential hits and carried out systematic similarity search trials. We find that the more complex reference molecules are, the lower the search performance becomes. However, a major result has been that random deletion of bits that are set on in fingerprints of complex reference molecules generally improves compound recall, although these random bit density reductions also cause a loss in chemical information content. These results suggest a general search strategy for fingerprints that are sensitive to complexity effects when optimized active compounds are used as reference molecules.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
1747-0285
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
71
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
511-7
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Random reduction in fingerprint bit density improves compound recall in search calculations using complex reference molecules.
pubmed:affiliation
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität Bonn, Dahlmannstr. 2, D-53113 Bonn, Germany.
pubmed:publicationType
Journal Article