Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.2403
DC FieldValueLanguage
dc.contributor.authorMüller, Simon-
dc.date.accessioned2019-09-12T13:24:15Z-
dc.date.available2019-09-12T13:24:15Z-
dc.date.issued2019-08-20-
dc.identifier.citationJournal of Cheminformatics 1 (11): Art.-Nr. 57 (2019)de_DE
dc.identifier.issn1758-2946de_DE
dc.identifier.urihttp://hdl.handle.net/11420/3353-
dc.description.abstractA priori calculation of thermophysical properties and predictive thermodynamic models can be very helpful for developing new industrial processes. Group contribution methods link the target property to contributions based on chemical groups or other molecular subunits of a given molecule. However, the fragmentation of the molecule into its subunits is usually done manually impeding the fast testing and development of new group contribution methods based on large databases of molecules. The aim of this work is to develop strategies to overcome the challenges that arise when attempting to fragment molecules automatically while keeping the definition of the groups as simple as possible. Furthermore, these strategies are implemented in two fragmentation algorithms. The first algorithm finds only one solution while the second algorithm finds all possible fragmentations. Both algorithms are tested to fragment a database of 20,000+ molecules for use with the group contribution model Universal Quasichemical Functional Group Activity Coefficients (UNIFAC). Comparison of the results with a reference database shows that both algorithms are capable of successfully fragmenting all the molecules automatically. Furthermore, when applying them on a larger database it is shown, that the newly developed algorithms are capable of fragmenting structures previously thought not possible to fragment.en
dc.description.sponsorshipDeutsche Forschungsgemeinschaft (DFG)de_DE
dc.language.isoende_DE
dc.publisherBioMed Centralde_DE
dc.relation.ispartofJournal of cheminformaticsde_DE
dc.rightsCC BY 4.0de_DE
dc.subjectMolecule fragmentationde_DE
dc.subjectCheminformaticsde_DE
dc.subjectRDKitde_DE
dc.subjectProperty predictionde_DE
dc.subjectGroup contribution methodde_DE
dc.subjectUNIFACde_DE
dc.subjectIncrementationde_DE
dc.subject.ddc510: Mathematikde_DE
dc.subject.ddc540: Chemiede_DE
dc.titleFlexible heuristic algorithm for automatic molecule fragmentation : application to the UNIFAC group contribution modelde_DE
dc.typeArticlede_DE
dc.identifier.urnurn:nbn:de:gbv:830-882.048833-
dc.identifier.doi10.15480/882.2403-
dc.type.diniarticle-
dc.subject.ddccode510-
dc.subject.ddccode540-
dcterms.DCMITypeText-
tuhh.identifier.urnurn:nbn:de:gbv:830-882.048833-
tuhh.oai.showtruede_DE
tuhh.abstract.englishA priori calculation of thermophysical properties and predictive thermodynamic models can be very helpful for developing new industrial processes. Group contribution methods link the target property to contributions based on chemical groups or other molecular subunits of a given molecule. However, the fragmentation of the molecule into its subunits is usually done manually impeding the fast testing and development of new group contribution methods based on large databases of molecules. The aim of this work is to develop strategies to overcome the challenges that arise when attempting to fragment molecules automatically while keeping the definition of the groups as simple as possible. Furthermore, these strategies are implemented in two fragmentation algorithms. The first algorithm finds only one solution while the second algorithm finds all possible fragmentations. Both algorithms are tested to fragment a database of 20,000+ molecules for use with the group contribution model Universal Quasichemical Functional Group Activity Coefficients (UNIFAC). Comparison of the results with a reference database shows that both algorithms are capable of successfully fragmenting all the molecules automatically. Furthermore, when applying them on a larger database it is shown, that the newly developed algorithms are capable of fragmenting structures previously thought not possible to fragment.de_DE
tuhh.publisher.doi10.1186/s13321-019-0382-3-
tuhh.publication.instituteThermische Verfahrenstechnik V-8de_DE
tuhh.identifier.doi10.15480/882.2403-
tuhh.type.opus(wissenschaftlicher) Artikel-
tuhh.institute.germanThermische Verfahrenstechnik V-8de
tuhh.institute.englishThermische Verfahrenstechnik V-8de_DE
tuhh.gvk.hasppnfalse-
dc.type.driverarticle-
dc.rights.cchttps://creativecommons.org/licenses/by/4.0/de_DE
dc.type.casraiJournal Article-
tuhh.container.issue1de_DE
tuhh.container.volume11de_DE
dc.relation.projectOpen Access Publizieren 2018 - 2019 / TU Hamburgde_DE
dc.rights.nationallicensefalsede_DE
tuhh.container.articlenumber57de_DE
item.languageiso639-1other-
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.creatorOrcidMüller, Simon-
item.creatorGNDMüller, Simon-
crisitem.author.deptThermische Verfahrenstechnik V-8-
crisitem.author.orcid0000-0003-1684-6994-
crisitem.author.parentorgStudiendekanat Verfahrenstechnik-
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