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Nalidixic Acid: an Antibacterial Paradox

Open access
Crumplin, G. C., Smith, J. T.·1975·Antimicrobial Agents and Chemotherapy

Abstract

Nalidixic acid was found to be most bactericidal against various species of gram-negative bacteria at 50 to 200 μg/ml. With all species tested, increases in the concentration of nalidixic acid above this range reduced, rather than increased, its bactericidal effect so that, at levels in the region of 400 μg/ml, the drug was relatively bacteriostatic. Therefore, the mode of action of nalidixic acid at various concentrations was investigated. It was found that at the most bactericidal concentration deoxyribonucleic acid synthesis, but no ribonucleic acid (RNA) or protein synthesis, was inhibited. However at higher concentrations, where the drug is least bactericidal, both RNA and protein synthesis were found to be inhibited. Results are presented which suggest that the protein synthesis inhibition is a secondary manifestation of the ability of the drug to inhibit RNA synthesis, and that of RNA synthesis is most likely the second target site for the action of the drug when bacteria are exposed to it in high concentrations. The clinical implications of these findings are discussed.

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Metadata

Authors
Crumplin, G. C., & Smith, J. T.
Venue
Antimicrobial Agents and Chemotherapy
Published
1975-09
Volume
8
Issue
3
Pages
251-261
ISSN
  • 0066-4804 (ISSN-L)
  • 1098-6596
OpenAlex
W2005683797
Cited by
194
References
0
FWCI
0.89
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Nalidixic Acid: an Antibacterial Paradox. https://app.cochat.ai/papers/10.1128/aac.8.3.251
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Crumplin, G. C., & Smith, J. T. (1975). Nalidixic Acid: an Antibacterial Paradox. Antimicrobial Agents and Chemotherapy. https://doi.org/10.1128/aac.8.3.251

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.