Source:http://linkedlifedata.com/resource/pubmed/id/15625110
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
2
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| pubmed:dateCreated |
2005-1-12
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| pubmed:abstractText |
Establishing quantitative relationships between molecular structure and broad biological effects has been a longstanding challenge in science. Currently, no method exists for forecasting broad biological activity profiles of medicinal agents even within narrow boundaries of structurally similar molecules. Starting from the premise that biological activity results from the capacity of small organic molecules to modulate the activity of the proteome, we set out to investigate whether descriptor sets could be developed for measuring and quantifying this molecular property. Using a 1,567-compound database, we show that percent inhibition values, determined at single high drug concentration in a battery of in vitro assays representing a cross section of the proteome, provide precise molecular property descriptors that identify the structure of molecules. When broad biological activity of molecules is represented in spectra form, organic molecules can be sorted by quantifying differences between biological spectra. Unlike traditional structure-activity relationship methods, sorting of molecules by using biospectra comparisons does not require knowledge of a molecule's putative drug targets. To illustrate this finding, we selected as starting point the biological activity spectra of clotrimazole and tioconazole because their putative target, lanosterol demethylase (CYP51), was not included in the bioassay array. Spectra similarity obtained through profile similarity measurements and hierarchical clustering provided an unbiased means for establishing quantitative relationships between chemical structures and biological activity spectra. This methodology, which we have termed biological spectra analysis, provides the capability not only of sorting molecules on the basis of biospectra similarity but also of predicting simultaneous interactions of new molecules with multiple proteins.
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| pubmed:commentsCorrections |
http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-1036914,
http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-10462437,
http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-10499865,
http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-10891108,
http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-10926528,
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http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-11827826,
http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-11872830,
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http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-12088630,
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http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-14965296,
http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-15010543,
http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-3545213,
http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-8568818,
http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-9383411,
http://linkedlifedata.com/resource/pubmed/commentcorrection/15625110-9538517
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:citationSubset |
IM
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| pubmed:chemical | |
| pubmed:status |
MEDLINE
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| pubmed:month |
Jan
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| pubmed:issn |
0027-8424
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| pubmed:author | |
| pubmed:issnType |
Print
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| pubmed:day |
11
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| pubmed:volume |
102
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
261-6
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| pubmed:dateRevised |
2009-11-18
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| pubmed:meshHeading | |
| pubmed:year |
2005
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| pubmed:articleTitle |
Biological spectra analysis: Linking biological activity profiles to molecular structure.
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| pubmed:affiliation |
Pfizer Global Research and Development, Groton, CT 06340, USA.
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| pubmed:publicationType |
Journal Article
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