EventsMOL2NET'20, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 6th ed.
Event submissions
Published
with-doi10.3390/mol2net-06-09176 (registering DOI)
This submission belongs to the session 09. USEDAT-06: USA-Europe Data Analysis Training Program Workshop, Bilbao, Spain-Cambridge, UK-Miami, USA, 2020 of the event MOL2NET'20, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 6th ed.
Published date
18 Jan, 2021
Citation
Jose I. Bueso-Bordils, Pedro A. Alemán-López, Beatriz Suay-Garcia, Rafael Martín-Algarra, Maria J. Duart, Antonio Falcó, Gerardo M. Antón-Fos, Discriminant Equations for the Search of New Anti-MRSA Drugs, in Proceedings of MOL2NET'20, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 6th ed., 30 January 2020–30 January 2021, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-06-09176
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Discriminant Equations for the Search of New Anti-MRSA Drugs

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Jose I. Bueso-Bordils 1
Pedro A. Alemán-López 1
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Beatriz Suay-Garcia 2
Rafael Martín-Algarra 1
Maria J. Duart 1
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Antonio Falcó 3
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Gerardo M. Antón-Fos 1
1. Departamento de Farmacia, Universidad Cardenal Herrera-CEU, CEU Universities C/ Ramón y Cajal s/n, 46115 Alfara del Patriarca (Valencia), Spain
2. ESI International Chair@CEU-UCH,Departamento de Matemáticas, Física y Ciencias Tecnológicas, Universidad Cardenal Herrera-CEU, CEU Universities San Bartolomé 55, 46115 Alfara del Patriarca (Valencia), Spain
3. ESI International Chair@CEU-UCH,Departamento de Matemáticas, Física y Ciencias Tecnológicas, Universidad Cardenal Herrera-CEU, CEU Universities San Bartolomé 55, 46115 Alfara del Patriarca (Valencia), Spain
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 a habitual resident of hospitals, where it causes a problem of multidrug resistance.

In this study, molecular topology was used 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 to 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.

Keywords
antibacterial
antibiotics
anti-MRSA
computational chemistry
linear discriminant analysis
molecular topology
molecular connectivity
topological indices
quinolones
QSAR
Manuscript
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