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Molecular topology for the search of new anti-MRSA compounds


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Title: Molecular topology for the search of new anti-MRSA compounds
Authors : Bueso Bordils, José Ignacio
Alemán López, Pedro
Martín Algarra, Rafael Vicente
Duart Duart, María José
Falcó Montesinos, Antonio
Antón Fos, Gerardo Manuel
Keywords: Estafilococos - Resistencia a los medicamentos - Modelos matemáticos.Topología - Aplicaciones en moléculas.Quinolone antibacterial agents - Mathematical models.Quinolonas - Modelos matemáticos.Topology in molecules.Staphylococcus - Drug resistance - Mathematical models.
Publisher: MDPI
Citation: Bueso-Bordils, J. I., Alemán-López, P. A., Martín-Algarra, R., Duart, M. J., Falcó, A. & Antón-Fos, G. M. (2021). Molecular topology for the search of new anti-MRSA compounds. International Journal of Molecular Sciences, vol. 22, i. 11 (29 may.), art. 5823. DOI: https://doi.org/10.3390/ijms22115823
Abstract: The variability of methicillin-resistant Staphylococcus aureus (MRSA), its rapid adaptive response against environmental changes, and its continued acquisition of antibiotic resistance determinants have made it commonplace in hospitals, where it causes the problem of multidrug resistance. In this study, we used molecular topology to develop several discriminant equations capable of classifying compounds according to their anti-MRSA activity. Topological indices were used as structural descriptors and their relationship with anti-MRSA activity was determined by applying linear discriminant analysis (LDA) on a group of quinolones and quinolone-like compounds. Four extra equations were constructed, named DFMRSA1, DFMRSA2, DFMRSA3 and DFMRSA4 (DFMRSA was built in a previous study), all with good statistical parameters, such as Fisher–Snedecor F (>68 in all cases), Wilk’s lambda (<0.13 in all cases), and percentage of correct classification (>94% in all cases), which allows a reliable extrapolation prediction of antibacterial activity in any organic compound. The results obtained clearly reveal the high efficiency of combining molecular topology with LDA for the prediction of anti-MRSA activity.
Description: Este artículo se encuentra disponible en la siguiente URL: https://www.mdpi.com/1422-0067/22/11/5823
Este artículo de investigación pertenece al número especial "Complex Networks, Bio-Molecular Systems, and Machine Learning".
URI: http://hdl.handle.net/10637/13577
Rights : http://creativecommons.org/licenses/by/4.0/deed.es
ISSN: 1422-0067 (Electrónico)
Issue Date: 29-May-2021
Center : Universidad Cardenal Herrera-CEU
Appears in Collections:Dpto. Farmacia





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