EventsMOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed.
Event submissions
Published
with-doi10.3390/mol2net-05-06775
This submission belongs to the session 03. NICEXSM-05: North-Ibero-American Congress on Exp. and Simul. Methods, Valencia, Bilbao, Spain-Miami, USA, 2019 of the event MOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed.
Published date
15 Jan, 2020
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 Antibacterial Drugs, in Proceedings of MOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed., 20 March–20 December 2019, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-05-06775
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Discriminant Equations for the Search of New Antibacterial 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

In this study, molecular topology was used to develop several discriminant equations capable of classifying compounds according to their antibacterial activity.

Topological indices were used as structural descriptors and their relation to antibacterial activity was determined by applying linear discriminant analysis (LDA) on a group of quinolones and quinolone-like compounds.

Four extra equations were constructed, named DF3, DF4, DF5 and DF6 (DF1 and DF2 were built in a previous study), all with good statistical parameters such as Fisher-Snedecor F (> 25 in all cases), Wilk’s lambda (< 0.36 in all cases) and percentage of correct classification (> 80 % 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 antibacterial activity.

Keywords
Antibacterial
antibiotics
computational chemistry
linear discriminant analysis
molecular topology
molecular connectivity
topological indices
quinolones
QSAR
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