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Identification of a Family of Glycoside Derivatives Biologically Active against Acinetobacter baumannii and Other MDR Bacteria Using a QSPR Model

As the rate of discovery of new antibacterial compounds for multidrug-resistant bacteria is declining, there is an urge for the search for molecules that could revert this tendency. Acinetobacter baumannii has emerged as a highly virulent Gram-negative bacterium that has acquired multiple resistance...

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Autores principales: Palacios-Can, Francisco José, Silva-Sánchez, Jesús, León-Rivera, Ismael, Tlahuext, Hugo, Pastor, Nina, Razo-Hernández, Rodrigo Said
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9964118/
https://www.ncbi.nlm.nih.gov/pubmed/37259397
http://dx.doi.org/10.3390/ph16020250
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author Palacios-Can, Francisco José
Silva-Sánchez, Jesús
León-Rivera, Ismael
Tlahuext, Hugo
Pastor, Nina
Razo-Hernández, Rodrigo Said
author_facet Palacios-Can, Francisco José
Silva-Sánchez, Jesús
León-Rivera, Ismael
Tlahuext, Hugo
Pastor, Nina
Razo-Hernández, Rodrigo Said
author_sort Palacios-Can, Francisco José
collection PubMed
description As the rate of discovery of new antibacterial compounds for multidrug-resistant bacteria is declining, there is an urge for the search for molecules that could revert this tendency. Acinetobacter baumannii has emerged as a highly virulent Gram-negative bacterium that has acquired multiple resistance mechanisms against antibiotics and is considered of critical priority. In this work, we developed a quantitative structure-property relationship (QSPR) model with 592 compounds for the identification of structural parameters related to their property as antibacterial agents against A. baumannii. QSPR mathematical validation ([Formula: see text] = 70.27, [Formula: see text] = −0.008, [Formula: see text] = 0.014, and [Formula: see text] = 0.021) and its prediction ability ([Formula: see text] (LMO)= 67.89, [Formula: see text] (EXT) = 67.75, [Formula: see text] = −0.068, [Formula: see text] = 0.0, [Formula: see text] = 0.229, and [Formula: see text] = 0.522) were obtained with different statistical parameters; additional validation was done using three sets of external molecules ([Formula: see text] = 72.89, 71.64 and 71.56). We used the QSPR model to perform a virtual screening on the BIOFACQUIM natural product database. From this screening, our model showed that molecules 32 to 35 and 54 to 68, isolated from different extracts of plants of the Ipomoea sp., are potential antibacterials against A. baumannii. Furthermore, biological assays showed that molecules 56 and 60 to 64 have a wide antibacterial activity against clinically isolated strains of A. baumannii, as well as other multidrug-resistant bacteria, including Staphylococcus aureus, Escherichia coli, Klebsiella pneumonia, and Pseudomonas aeruginosa. Finally, we propose 60 as a potential lead compound due to its broad-spectrum activity and its structural simplicity. Therefore, our QSPR model can be used as a tool for the investigation and search for new antibacterial compounds against A. baumannii.
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spelling pubmed-99641182023-02-26 Identification of a Family of Glycoside Derivatives Biologically Active against Acinetobacter baumannii and Other MDR Bacteria Using a QSPR Model Palacios-Can, Francisco José Silva-Sánchez, Jesús León-Rivera, Ismael Tlahuext, Hugo Pastor, Nina Razo-Hernández, Rodrigo Said Pharmaceuticals (Basel) Article As the rate of discovery of new antibacterial compounds for multidrug-resistant bacteria is declining, there is an urge for the search for molecules that could revert this tendency. Acinetobacter baumannii has emerged as a highly virulent Gram-negative bacterium that has acquired multiple resistance mechanisms against antibiotics and is considered of critical priority. In this work, we developed a quantitative structure-property relationship (QSPR) model with 592 compounds for the identification of structural parameters related to their property as antibacterial agents against A. baumannii. QSPR mathematical validation ([Formula: see text] = 70.27, [Formula: see text] = −0.008, [Formula: see text] = 0.014, and [Formula: see text] = 0.021) and its prediction ability ([Formula: see text] (LMO)= 67.89, [Formula: see text] (EXT) = 67.75, [Formula: see text] = −0.068, [Formula: see text] = 0.0, [Formula: see text] = 0.229, and [Formula: see text] = 0.522) were obtained with different statistical parameters; additional validation was done using three sets of external molecules ([Formula: see text] = 72.89, 71.64 and 71.56). We used the QSPR model to perform a virtual screening on the BIOFACQUIM natural product database. From this screening, our model showed that molecules 32 to 35 and 54 to 68, isolated from different extracts of plants of the Ipomoea sp., are potential antibacterials against A. baumannii. Furthermore, biological assays showed that molecules 56 and 60 to 64 have a wide antibacterial activity against clinically isolated strains of A. baumannii, as well as other multidrug-resistant bacteria, including Staphylococcus aureus, Escherichia coli, Klebsiella pneumonia, and Pseudomonas aeruginosa. Finally, we propose 60 as a potential lead compound due to its broad-spectrum activity and its structural simplicity. Therefore, our QSPR model can be used as a tool for the investigation and search for new antibacterial compounds against A. baumannii. MDPI 2023-02-07 /pmc/articles/PMC9964118/ /pubmed/37259397 http://dx.doi.org/10.3390/ph16020250 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Palacios-Can, Francisco José
Silva-Sánchez, Jesús
León-Rivera, Ismael
Tlahuext, Hugo
Pastor, Nina
Razo-Hernández, Rodrigo Said
Identification of a Family of Glycoside Derivatives Biologically Active against Acinetobacter baumannii and Other MDR Bacteria Using a QSPR Model
title Identification of a Family of Glycoside Derivatives Biologically Active against Acinetobacter baumannii and Other MDR Bacteria Using a QSPR Model
title_full Identification of a Family of Glycoside Derivatives Biologically Active against Acinetobacter baumannii and Other MDR Bacteria Using a QSPR Model
title_fullStr Identification of a Family of Glycoside Derivatives Biologically Active against Acinetobacter baumannii and Other MDR Bacteria Using a QSPR Model
title_full_unstemmed Identification of a Family of Glycoside Derivatives Biologically Active against Acinetobacter baumannii and Other MDR Bacteria Using a QSPR Model
title_short Identification of a Family of Glycoside Derivatives Biologically Active against Acinetobacter baumannii and Other MDR Bacteria Using a QSPR Model
title_sort identification of a family of glycoside derivatives biologically active against acinetobacter baumannii and other mdr bacteria using a qspr model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9964118/
https://www.ncbi.nlm.nih.gov/pubmed/37259397
http://dx.doi.org/10.3390/ph16020250
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