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Title: Molecular descriptor data explain market prices of a large commercial chemical compound library
Authors: Polański, Jarosław
Kucia, Urszula
Duszkiewicz, Roksana
Kurczyk, Agata
Magdziarz, Tomasz
Gasteiger, Johann
Keywords: Medicinal chemistry; Efficiency; Big data in chemistry
Issue Date: 2016
Citation: Scientific Reports, 2016, no. 6, art. no. 28521
Abstract: The 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.
DOI: 10.1038/srep28521
ISSN: 2045-2322
Appears in Collections:Artykuły (WNŚiT)

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