PseudoResistance DB: A new Database of antibiotics related to Pseudomonas aeruginosa antibiotic resistance

Antibiotic resistance represents a significant challenge to global health, compromising the effectiveness of treatments. Pseudomonas aeruginosa, an opportunistic Gram-negative bacterium, is a priority pathogenic agent for research, being categorized as critical level by the World Health Organization (WHO) for the development of new therapeutic strategies. The antibiotics listed were screened through text mining correlated with P. aeruginosa of the Scielo database. The final database contains 98 antibiotics, containing textual information, Protein Data Bank, Partial Charge & Atom Type (PDBQT), Simplified Molecular Input Line Entry System (SMI), IUPAC International Chemical Identifier (INCHI), Molecular Design Limited Molfile (MOL2), Structure-Data File (SDF), Chemical Markup Language (CML), Cartesian Coordinates File (XYZ), Scalable Vector Graphics (SVG), Molecular File (MOL) and Protein Data Bank (PDB), converted using OpenBabel.

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Publication Details

Journal
Latin American Data in Science
Published
2025-09-15
DOI
https://doi.org/10.53805/lads.v5i1.69
Primary Topic
Antibiotic Resistance in Bacteria
Type
article
Field-Weighted Citation Impact
0.00

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article

PseudoResistance DB: A new Database of antibiotics related to Pseudomonas aeruginosa antibiotic resistance

Cristina Bormio-Nunes, Manuela Leal da Silva, Vinnícius Machado Schelk Gomes, Caio Cheohen
Latin American Data in Science
Antibiotic Resistance in Bacteria
article

PseudoResistance DB: A new Database of antibiotics related to Pseudomonas aeruginosa antibiotic resistance

Cristina Bormio-Nunes, Manuela Leal da Silva, Vinnícius Machado Schelk Gomes, Caio Cheohen
article en

Abstract

Antibiotic resistance represents a significant challenge to global health, compromising the effectiveness of treatments. Pseudomonas aeruginosa, an opportunistic Gram-negative bacterium, is a priority pathogenic agent for research, being categorized as critical level by the World Health Organization (WHO) for the development of new therapeutic strategies. The antibiotics listed were screened through text mining correlated with P. aeruginosa of the Scielo database. The final database contains 98 antibiotics, containing textual information, Protein Data Bank, Partial Charge & Atom Type (PDBQT), Simplified Molecular Input Line Entry System (SMI), IUPAC International Chemical Identifier (INCHI), Molecular Design Limited Molfile (MOL2), Structure-Data File (SDF), Chemical Markup Language (CML), Cartesian Coordinates File (XYZ), Scalable Vector Graphics (SVG), Molecular File (MOL) and Protein Data Bank (PDB), converted using OpenBabel.

Latin American Data in ScienceVol. 5(1)
Universidade Federal do Rio de Janeiro (BR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro
Openalex Percentile: Top 80%
Antibiotic Resistance in Bacteria
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