Retapamulin 1% ointment
Retapamulin, marketed by GlaxoSmithKline as the ointment Altabax, is an antibiotic for skin infections like impetigo.
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1 branded products available
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Similarity is based on WHO Anatomical Therapeutic Chemical (ATC) classification and on a factual NHS dm+d therapeutic-grouping code prefix. Source data: NHS dm+d via TRUD (OGL v3.0), WHO ATC/DDD Index.
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SNOMED CT and dm+d codes from NHS TRUD (Technology Reference data Update Distribution), licensed under the Open Government Licence v3.0. BNF code shown is the factual mapping value distributed by NHS Business Services Authority (NHSBSA) in the dm+d supplementary file under OGL v3.0; it is not affiliated with, nor licensed from, the publishers of the British National Formulary. ATC codes from the WHO Collaborating Centre for Drug Statistics Methodology (whocc.no).
Active and completed clinical studies from ClinicalTrials.gov
Source: ClinicalTrials.gov, a database of the U.S. National Library of Medicine (NLM), National Institutes of Health (NIH). Data accessed via ClinicalTrials.gov API v2. Trial information is provided for research purposes and does not constitute medical advice.
Academic studies and reviews for this medicine's active substance
Showing all 13 studies.
2019–2026
Showing all 13 studies, sorted by most relevant.
Sezen Meydan, J. Marks, D. Klepacki, et al.
Molecular cell, 2019
Sun P, Cui M, Jing J, et al.
2023
- Bacterial Infections
- Sepsis
- Escherichia coli
BACKGROUND: Sepsis is a life-threatening organ dysfunction caused by abnormal immune responses to various, predominantly bacterial, infections. Different bacterial infections lead to substantial variation in disease manifestation and therapeutic strategies. However, the underlying cellular heterogeneity and mechanisms involved remain poorly understood. METHODS: Multiple bulk transcriptome datasets from septic patients with 12 types of bacterial infections were integrated to identify signature genes for each infection. Signature genes were mapped onto an integrated large single-cell RNA (scRNA) dataset from septic patients, to identify subsets of cells associated with different sepsis types, and multiple omics datasets were combined to reveal the underlying molecular mechanisms. In addition, an scRNA dataset and spatial transcriptome data were used to identify signaling pathways in sepsis-related cells. Finally, molecular screening, optimization, and de novo design were conducted to identify potential targeted drugs and compounds. RESULTS: We elucidated the cellular heterogeneity among septic patients with different bacterial infections. In Escherichia coli (E. coli) sepsis, 19 signature genes involved in epigenetic regulation and metabolism were identified, of which DRAM1 was demonstrated to promote autophagy and glycolysis in response to E. coli infection. DRAM1 upregulation was confirmed in an independent sepsis cohort. Further, we showed that DRAM1 could maintain survival of a pro-inflammatory monocyte subset, C10_ULK1, which induces systemic inflammation by interacting with other cell subsets via resistin and integrin signaling pathways in blood and kidney tissue, respectively. Finally, retapamulin was identified and optimized as a potential drug for treatment of E. coli sepsis targeting the signature gene, DRAM1, and inhibiting E. coli protein synthesis. Several other targeted drugs were also identified in other types of sepsis, including nystatin targeting C1QA in Neisseria sepsis and dalfopristin targeting CTSD in Streptococcus viridans sepsis. CONCLUSION: Our study provides a comprehensive overview of the cellular heterogeneity and underlying mechanisms in septic patients with various bacterial infections, providing insights to inform development of stratified targeted therapies for sepsis.
Abstract licence: CC BY
García-Castillo M, Hernández-García M, Correa A, et al.
2024
Abstract Objectives We performed a multicentre study (2020–2022) to compare the in vitro activity of ozenoxacin and comparator agents against Staphylococcus aureus and Streptococcus pyogenes clinical isolates from skin and soft-tissue infections (SSTI). Methods A total of 1725 isolates (1454 S. aureus and 271 S. pyogenes) were collected in 10 centres from eight countries between January 2020 and December 2022. Antimicrobial susceptibility testing was determined (microdilution-SENSITITRE). Results were interpreted following European Committee on Antimicrobial Susceptibility Testing (EUCAST) 2023 (clinical breakpoints, ECOFF) and CLSI criteria. Results Ozenoxacin exhibited high in vitro activity against S. aureus (MIC50/90 = 0.002/0.12 mg/L) and S. pyogenes (MIC50/90 = 0.015/0.03 mg/L), inhibiting 99% of the isolates at MIC ≤ 0.5 mg/L and at MIC ≤ 0.06, respectively. The most active comparators against S. aureus were retapamulin (MIC90 = 0.12 mg/L), fusidic acid (MIC90 = 0.25 mg/L) and mupirocin (MIC90 = 0.5 mg/L); and against S. pyogenes were retapamulin (MIC90 = 0.03 mg/L), clindamycin (MIC90 = 0.12 mg/L) and mupirocin (MIC90 = 0.25 mg/L). Ciprofloxacin and methicillin resistant rates for S. aureus were 31.3% (455/1454) and 41% (598/1454), respectively. Additionally, 62% (373/598) of the MRSA were also ciprofloxacin non-susceptible, whereas only 10% (23/271) of the MSSA were ciprofloxacin resistant. Ozenoxacin was more active against ciprofloxacin-susceptible S. aureus than against ciprofloxacin-resistant isolates, and showed a slightly higher MIC in MRSA isolates than in MSSA. However, ozenoxacin activity was comparable in both ciprofloxacin-resistant MSSA and MRSA subsets. On the other hand, ozenoxacin had similar activity in ciprofloxacin-susceptible and resistant S. pyogenes isolates. Conclusions Ozenoxacin is a potent antimicrobial agent of topic use against Gram-positive bacteria causing SSTI, including MRSA isolates non-susceptible to ciprofloxacin.
Abstract licence: CC BY
S. Bello, M. Imam, Muhammad Bashir Bello, et al.
Frontiers in Cellular and Infection Microbiology, 2023
- COVID-19
- SARS-CoV-2
- COVID-19 Vaccines
Background Although tremendous success has been achieved in the development and deployment of effective COVID-19 vaccines, developing effective therapeutics for the treatment of those who do come down with the disease has been with limited success. To repurpose existing drugs for COVID-19, we previously showed, qualitatively, that erythromycin, retapamulin, pyridoxine, folic acid, and ivermectin inhibit SARS-COV-2-induced cytopathic effect (CPE) in Vero cells. Aim This study aimed to quantitatively explore the inhibition of SARS-CoV-2-induced CPE by erythromycin, retapamulin, pyridoxine, folic acid, and ivermectin and to determine the effect of these drugs on SARS-CoV-2 papain-like protease and 3CL protease (M PRO ) enzymes. Methods Neutral red (3-amino-7-dimethylamino-2-methyl-phenazine hydrochloride) cell viability assay was used to quantify CPE after infecting pre-treated Vero cells with clinical SARS-Cov-2 isolates. Furthermore, SensoLyte ® 520 SARS-CoV-2 papain-like protease and SensoLyte ® 520 SARS-CoV-2 M PRO activity assay kits were used to evaluate the inhibitory activity of the drugs on the respective enzymes. Results Erythromycin, retapamulin, pyridoxine, folic acid, and ivermectin dose-dependently inhibit SARS-CoV-2-induced CPE in Vero cells, with inhibitory concentration-50 (IC 50 ) values of 3.27 µM, 4.23 µM, 9.29 µM, 3.19 µM, and 84.31 µM, respectively. Furthermore, erythromycin, retapamulin, pyridoxine, folic acid, and ivermectin dose-dependently inhibited SARS-CoV-2 papain-like protease with IC 50 values of 0.94 µM, 0.88 µM, 1.14 µM, 1.07 µM, and 1.51 µM, respectively, and inhibited the main protease (M PRO ) with IC 50 values of 1.35 µM, 1.25 µM, 7.36 µM, 1.15 µM, and 2.44 µM, respectively. Conclusion The IC 50 for all the drugs, except ivermectin, was at the clinically achievable plasma concentration in humans, which supports a possible role for the drugs in the management of COVID-19. The lack of inhibition of CPE by ivermectin at clinical concentrations could be part of the explanation for its lack of effectiveness in clinical trials.
Abstract licence: CC BY
Shaibu Oricha Bello, Shaibu Oricha Bello, Shaibu Oricha Bello, et al.
Frontiers in Pharmacology, 2023
Several efforts to repurpose drugs for COVID-19 treatment have largely either failed to identify a suitable agent or agents identified did not translate to clinical use. Reasons that have been suggested to explain the failures include use of inappropriate doses, that are not clinically achievable, in the screening experiments, and the use of inappropriate pre-clinical laboratory surrogates to predict efficacy. In this study, we used an innovative algorithm, that incorporates dissemination and implementation considerations, to identify potential drugs for COVID-19 using iterative computational and wet laboratory methods. The drugs were screened at doses that are known to be achievable in humans. Furthermore, inhibition of viral induced cytopathic effect (CPE) was used as the laboratory surrogate to predict efficacy. Erythromycin, pyridoxine, folic acid and retapamulin were found to inhibit SARS-CoV-2 induced CPE in Vero cells at concentrations that are clinically achievable. Additional studies may be required to further characterize the inhibitions of CPE and the possible mechanisms.
Abstract licence: CC BY
Igor Fijalkowski, Valdes Snauwaert, Petra Van Damme
mBio, 2024
- Ribosomes
- Proteome
- Protein Biosynthesis
ABSTRACT In recent years, it has become evident that the true complexity of bacterial proteomes remains underestimated. Gene annotation tools are known to propagate biases and overlook certain classes of truly expressed proteins, particularly proteoforms—protein isoforms arising from a single gene. Recent (re-)annotation efforts heavily rely on ribosome profiling by providing a direct readout of translation to fully describe bacterial proteomes. In this study, we employ a robust riboproteogenomic pipeline to conduct a systematic census of expressed N-terminal proteoform pairs, representing two isoforms encoded by a single gene raised by annotated and alternative translation initiation, in Salmonella . Intriguingly, conditional-dependent changes in relative utilization of annotated and alternative translation initiation sites (TIS) were observed in several cases. This suggests that TIS selection is subject to regulatory control, adding yet another layer of complexity to our understanding of bacterial proteomes. IMPORTANCE With the emerging theme of genes within genes comprising the existence of alternative open reading frames (ORFs) generated by translation initiation at in-frame start codons, mechanisms that control the relative utilization of annotated and alternative TIS need to be unraveled and our molecular understanding of resulting proteoforms broadened. Utilizing complementary ribosome profiling strategies to map ORF boundaries, we uncovered dual-encoding ORFs generated by in-frame TIS usage in Salmonella . Besides demonstrating that alternative TIS usage may generate proteoforms with different characteristics, such as differential localization and specialized function, quantitative aspects of conditional retapamulin-assisted ribosome profiling (Ribo-RET) translation initiation maps offer unprecedented insights into the relative utilization of annotated and alternative TIS, enabling the exploration of gene regulatory mechanisms that control TIS usage and, consequently, the translation of N-terminal proteoform pairs.
Abstract licence: CC BY
Fabian Audu Ugbe, Gideon Adamu Shallangwa, Adamu Uzairu, et al.
Borneo Journal of Pharmacy, 2023
Filariasis (Lymphatic filariasis and Onchocerciasis) is a common neglected tropical disease caused by parasitic nematodes called filarial worms, which often host the Wolbachia bacteria. A good treatment approach seeks Wolbachia as a drug target. Here, a computer-aided design of some boron-pleuromutilin analogs was conducted using the ligand-based drug design approach while performing molecular docking investigation and pharmacokinetics analyses to evaluate their drug-likeness properties. The newly designed compounds (49a, 49b, and 49c) showed improved inhibitory activities (pEC50) over those of the template and the clinically relevant pleuromutilins (retapamulin and lefamulin) in the order; 49b (pEC50 = 9.0409) > 49c (8.8175) > 49a (8.5930) > template (49) (8.4222) > retapamulin (6.7403) > lefamulin (6.1369). Standard docking performed with OTU deubiquitinase (6W9O) revealed the order of binding energies; 49c (-88.07 kcal/mol) > 49b (-84.26 kcal/mol) > doxycycline (-83.70 kcal/mol) > template (-82.57 kcal/mol) > 49a (-78.43 kcal/mol) > lefamulin (-76.83 kcal/mol) > retapamulin (-76.78 kcal/mol), with the new compounds all showing good pharmacological interactions with the receptor’s amino acids. The new analogs were also predicted to be orally bioavailable with better pharmacokinetic profiles than the template, retapamulin, lefamulin, and doxycycline having no more than one violation of Lipinski’s ROF. Therefore, the newly designed compounds could be considered potential anti-filarial drug candidates.
Abstract licence: CC BY-SA
H. Paternoga, B. Beckert, D.N. Wilson
Worldwide Protein Data Bank, 2023
Y. Ando, O. Nureki, Y. Itoh
Worldwide Protein Data Bank, 2025
Deependra Singh, Manju Rawat Singh, Sunil Kumar Kadiri, Prashant Tiwari, Jitendra Yadav, Prabhat Kumar, V. Anitha Kumari, Nandimandalam Silpa, R. Venu Priya, P. Bharath Rathna Kumar, Rajni Kant Panik
ASSOC ADVANCEMENT ZOOLOGY , AZADANAGAR COLONY RUSTAMPUR, GORAKHPUR, INDIA, 273001, 2023
Sources: aggregated from Europe PMC (EMBL-EBI), OpenAlex, Crossref, PubMed and other open scholarly databases. Retracted articles are excluded. Study information is provided for research purposes and does not constitute medical advice.
Pharmacology and chemical data from DrugBank
Key facts
Drug status
Approved
Major interactions
None known
Half-life
Not available
Mechanism
Retapamulin is a bacterial protein synthesis inhibitor belonging to a class of compounds called pleuromutilins.
Food interactions
None known
Human targets
None mapped
Data: DrugBank · CC BY-NC 4.0
Pharmacokinetics at a glance
Protein binding
94%
Metabolism
Pharmacokinetic data: DrugBank · CC BY-NC 4.0
Known interactions with other medications. Always consult a healthcare professional.
Showing 50 of 387 interactions
How the body processes this drug — absorption, distribution, metabolism, and elimination
Enzymes involved in drug metabolism — important for understanding drug interactions
ATC D06AX13
Chemical identifiers
CAS, UNII, InChI Key and database cross-references
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Chemical identifiers
CAS, UNII, InChI Key and database cross-references
Linked compound data from DrugBank Open Data (CC BY-NC 4.0)
Retapamulin
Additional database identifiers
Drugs Product Database (DPD)
20196
ChemSpider
25064484
PDB
G34
ZINC
ZINC000100013500
GenBank Gene Database
AE006477
GenBank Protein Database
13621367
UniProt Accession
RL3_STRP1
HUGO Gene Nomenclature Committee (HGNC)
HGNC:2637
GenAtlas
CYP3A4
GeneCards
CYP3A4
GenBank Gene Database
M18907
Guide to Pharmacology
1337
UniProt Accession
CP3A4_HUMAN
DrugBank citations
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Structured knowledge from the free knowledge base
ATC classifications (Wikidata)
Linked open data from Wikidata (Q7316645), a free and open knowledge base operated by the Wikimedia Foundation. Data is available under the Creative Commons CC0 1.0 Public Domain Dedication. WHO INN from the World Health Organization.