Empirical modeling of the sodium channel inhibition caused by drugs

2012
book section
conference proceedings
dc.abstract.enThe aim of this work was to create extended QSAR model of the relationship between sodium channel blocking activity of the particular compound and its chemical structure together with the in vitro assay conditions. Artificial neural networks (ANNs) were chosen as modeling tools. Chemoinformatics software was used for calculation of the molecular descriptors describing the structure of the interest. Drug concentration causing 50% of the channel inhibition (IC50) was used as the modeling endpoint. The data was based on the literature search and consisted of 38 drugs and 108 records. Initial number of inputs was 110 and during the sensitivity analysis was reduced to 20. ANNs models were optimized in the extended 10-fold cross-validation scheme yielding RMSE = 0.68, NRMSE = 20.7% and R2= 0.35. Best models were ANNs ensembles combining three ANNs with their outputs averaged as a collective output of the system.pl
dc.affiliationWydział Nauk o Zdrowiu : Instytut Zdrowia Publicznegopl
dc.affiliationWydział Farmaceutyczny : Zakład Farmacji Społecznejpl
dc.affiliationWydział Farmaceutyczny : Zakład Technologii Postaci Leku i Biofarmacjipl
dc.contributor.authorMendyk, Aleksander - 130937 pl
dc.contributor.authorWiśniowska, Barbara - 148047 pl
dc.contributor.authorFijorek, Kamilpl
dc.contributor.authorGlinka, Annapl
dc.contributor.authorPolak, Maciej - 214572 pl
dc.contributor.authorSzlęk, Jakub - 162262 pl
dc.contributor.authorPolak, Sebastian - 133197 pl
dc.contributor.editorMurray, Alanpl
dc.date.accession2015-02-10pl
dc.date.accessioned2015-02-11T14:33:04Z
dc.date.available2015-02-11T14:33:04Z
dc.date.issued2012pl
dc.description.conftypeinternationalpl
dc.description.physical293-295pl
dc.description.seriesComputing in Cardiology
dc.description.seriesnumber39
dc.identifier.eisbn978-1-4673-2076-4pl
dc.identifier.isbn978-1-4673-2074-0pl
dc.identifier.serieseissn2325-887X
dc.identifier.seriesissn2325-8861
dc.identifier.urihttp://ruj.uj.edu.pl/xmlui/handle/item/3029
dc.identifier.weblinkhttp://www.cinc.org/archives/2012/pdf/0293.pdfpl
dc.languageengpl
dc.language.containerengpl
dc.pubinfoPiscataway : Institute of Electrical and Electronics Engineerspl
dc.rightsDodaję tylko opis bibliograficzny*
dc.rights.uri*
dc.subject.en10-fold cross-validationpl
dc.subject.ensodium channelpl
dc.subject.enliterature searchpl
dc.subject.enmolecular descriptorspl
dc.subject.enin-vitro assayspl
dc.subject.enempirical modelingpl
dc.subject.endrug concentrationpl
dc.subject.enchemoinformaticspl
dc.subtypeConferenceProceedingspl
dc.titleEmpirical modeling of the sodium channel inhibition caused by drugspl
dc.title.container39th Computing in Cardiology Conference (CinC), September 9-12, 2012, Kraków, Polandpl
dc.typeBookSectionpl
dspace.entity.typePublication
dc.abstract.enpl
The aim of this work was to create extended QSAR model of the relationship between sodium channel blocking activity of the particular compound and its chemical structure together with the in vitro assay conditions. Artificial neural networks (ANNs) were chosen as modeling tools. Chemoinformatics software was used for calculation of the molecular descriptors describing the structure of the interest. Drug concentration causing 50% of the channel inhibition (IC50) was used as the modeling endpoint. The data was based on the literature search and consisted of 38 drugs and 108 records. Initial number of inputs was 110 and during the sensitivity analysis was reduced to 20. ANNs models were optimized in the extended 10-fold cross-validation scheme yielding RMSE = 0.68, NRMSE = 20.7% and R2= 0.35. Best models were ANNs ensembles combining three ANNs with their outputs averaged as a collective output of the system.
dc.affiliationpl
Wydział Nauk o Zdrowiu : Instytut Zdrowia Publicznego
dc.affiliationpl
Wydział Farmaceutyczny : Zakład Farmacji Społecznej
dc.affiliationpl
Wydział Farmaceutyczny : Zakład Technologii Postaci Leku i Biofarmacji
dc.contributor.authorpl
Mendyk, Aleksander - 130937
dc.contributor.authorpl
Wiśniowska, Barbara - 148047
dc.contributor.authorpl
Fijorek, Kamil
dc.contributor.authorpl
Glinka, Anna
dc.contributor.authorpl
Polak, Maciej - 214572
dc.contributor.authorpl
Szlęk, Jakub - 162262
dc.contributor.authorpl
Polak, Sebastian - 133197
dc.contributor.editorpl
Murray, Alan
dc.date.accessionpl
2015-02-10
dc.date.accessioned
2015-02-11T14:33:04Z
dc.date.available
2015-02-11T14:33:04Z
dc.date.issuedpl
2012
dc.description.conftypepl
international
dc.description.physicalpl
293-295
dc.description.series
Computing in Cardiology
dc.description.seriesnumber
39
dc.identifier.eisbnpl
978-1-4673-2076-4
dc.identifier.isbnpl
978-1-4673-2074-0
dc.identifier.serieseissn
2325-887X
dc.identifier.seriesissn
2325-8861
dc.identifier.uri
http://ruj.uj.edu.pl/xmlui/handle/item/3029
dc.identifier.weblinkpl
http://www.cinc.org/archives/2012/pdf/0293.pdf
dc.languagepl
eng
dc.language.containerpl
eng
dc.pubinfopl
Piscataway : Institute of Electrical and Electronics Engineers
dc.rights*
Dodaję tylko opis bibliograficzny
dc.rights.uri*
dc.subject.enpl
10-fold cross-validation
dc.subject.enpl
sodium channel
dc.subject.enpl
literature search
dc.subject.enpl
molecular descriptors
dc.subject.enpl
in-vitro assays
dc.subject.enpl
empirical modeling
dc.subject.enpl
drug concentration
dc.subject.enpl
chemoinformatics
dc.subtypepl
ConferenceProceedings
dc.titlepl
Empirical modeling of the sodium channel inhibition caused by drugs
dc.title.containerpl
39th Computing in Cardiology Conference (CinC), September 9-12, 2012, Kraków, Poland
dc.typepl
BookSection
dspace.entity.type
Publication
Affiliations

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