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dc.contributor.otherUCH. Departamento de Matemáticas, Física y Ciencias Tecnológicas-
dc.contributor.otherUCH. Departamento de Farmacia-
dc.contributor.otherProducción Científica UCH 2020-
dc.creatorSuay García, Beatriz.-
dc.creatorFalcó Montesinos, Antonio.-
dc.creatorBueso Bordils, José Ignacio.-
dc.creatorAntón Fos, Gerardo Manuel.-
dc.creatorPérez Gracia, María Teresa.-
dc.creatorAlemán López, Pedro.-
dc.date2019-
dc.date.accessioned2021-05-08T04:00:11Z-
dc.date.available2021-05-08T04:00:11Z-
dc.date.issued2021-05-08-
dc.identifier.citationSuay-Garcia, B., Falcó, A., Bueso-Bordils, J.I., Anton-Fos, G.M., Pérez-Gracia, M.T. & Alemán-López, P.A. (2020). Tree-based QSAR model for drug repurposing in the discovery of new antibacterial compounds against "Escherichia coli". Pharmaceuticals, vol. 13, i. 12 (28 nov.), art. 431. DOI: https://doi.org/10.3390/ph13120431-
dc.identifier.issn1424-8247 (Electrónico).-
dc.identifier.urihttp://hdl.handle.net/10637/12573-
dc.descriptionEste artículo se encuentra disponible en la página web de la revista en la siguiente URL: https://www.mdpi.com/1424-8247/13/12/431-
dc.descriptionEste artículo pertenece a la colección "Old pharmaceuticals with new applications".-
dc.description.abstractDrug repurposing appears as an increasing popular tool in the search of new treatment options against bacteria. In this paper, a tree-based classification method using Linear Discriminant Analysis (LDA) and discrete indexes was used to create a QSAR (Quantitative Structure-Activity Relationship) model to predict antibacterial activity against Escherichia coli. The model consists on a hierarchical decision tree in which a discrete index is used to divide compounds into groups according to their values for said index in order to construct probability spaces. The second step consists in the calculation of a discriminant function which determines the prediction of the model. The model was used to screen the DrugBank database, identifying 134 drugs as possible antibacterial candidates. Out of these 134 drugs, 8 were antibacterial drugs, 67 were drugs approved for di erent pathologies and 55 were drugs in experimental stages. This methodology has proven to be a viable alternative to the traditional methods used to obtain prediction models based on LDA and its application provides interesting new drug candidates to be studied as repurposed antibacterial treatments. Furthermore, the topological indexes Nclass and Numhba have proven to have the ability to group active compounds e ectively, which suggests a close relationship between them and the antibacterial activity of compounds against E. coli.-
dc.formatapplication/pdf-
dc.language.isoen-
dc.publisherMDPI-
dc.relation.ispartofPharmaceuticals, vol. 13, n. 12.-
dc.rightshttp://creativecommons.org/licenses/by/4.0/deed.es-
dc.subjectAntibiotics - Mathematical models.-
dc.subjectDrug resistance in microorganisms - Mathematical models.-
dc.subjectPharmaceutical microbiology - Mathematical models.-
dc.subjectFarmacología molecular - Modelos matemáticos.-
dc.subjectBiología molecular - Modelos matemáticos.-
dc.subjectAntibióticos - Modelos matemáticos.-
dc.subjectEscherichia coli - Resistencia a los medicamentos - Modelos matemáticos.-
dc.subjectEscherichia coli - Drug resistance - Mathematical models.-
dc.subjectBacterias - Resistencia a los medicamentos - Modelos matemáticos.-
dc.subjectMolecular pharmacology - Mathematical models.-
dc.subjectMolecular biology - Mathematical models.-
dc.subjectMicrobiología farmacéutica - Modelos matemáticos.-
dc.titleTree-based QSAR Model for drug repurposing in the discovery of new antibacterial compounds against "Escherichia coli"-
dc.typeArtículo-
dc.identifier.doihttps://doi.org/10.3390/ph13120431-
Aparece en las colecciones: Dpto. Farmacia

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