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Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12128/3010
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dc.contributor.authorPolański, Jarosław-
dc.contributor.authorKucia, Urszula-
dc.contributor.authorDuszkiewicz, Roksana-
dc.contributor.authorKurczyk, Agata-
dc.contributor.authorMagdziarz, Tomasz-
dc.contributor.authorGasteiger, Johann-
dc.date.accessioned2018-04-23T05:58:04Z-
dc.date.available2018-04-23T05:58:04Z-
dc.date.issued2016-
dc.identifier.citationScientific Reports, 2016, no. 6, art. no. 28521pl_PL
dc.identifier.issn2045-2322-
dc.identifier.urihttp://hdl.handle.net/20.500.12128/3010-
dc.description.abstractThe relationship between the structure and a property of a chemical compound is an essential concept in chemistry guiding, for example, drug design. Actually, however, we need economic considerations to fully understand the fate of drugs on the market. We are performing here for the first time the exploration of quantitative structure-economy relationships (QSER) for a large dataset of a commercial building block library of over 2.2 million chemicals. This investigation provided molecular statistics that shows that on average what we are paying for is the quantity of matter. On the other side, the influence of synthetic availability scores is also revealed. Finally, we are buying substances by looking at the molecular graphs or molecular formulas. Thus, those molecules that have a higher number of atoms look more attractive and are, on average, also more expensive. Our study shows how data binning could be used as an informative method when analyzing big data in chemistry.pl_PL
dc.language.isoenpl_PL
dc.rightsUznanie autorstwa 3.0 Polska*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/pl/*
dc.subjectMedicinal chemistrypl_PL
dc.subjectEfficiencypl_PL
dc.subjectBig data in chemistrypl_PL
dc.titleMolecular descriptor data explain market prices of a large commercial chemical compound librarypl_PL
dc.typeinfo:eu-repo/semantics/articlepl_PL
dc.identifier.doi10.1038/srep28521-
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