Macrolides and associated antibiotics based on similar mechanism of action like lincosamides in malaria

Gaillard, Tiphaine; Dormoi, Jérôme; Madamet, Marylin; Pradines, Bruno

doi:10.1186/s12936-016-1114-z

Cited by 36 publications

(25 citation statements)

References 83 publications

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“…Antibiotics may exhibit antimalarial properties, albeit slow-acting, by targeting the apicoplast during development (Dahl et al, 2006 ; Barthel et al, 2008 ; Chakraborty, 2016 ). Macrolides are known for their effectiveness in treatment of uncomplicated malaria in combination with quinine, where the main mechanism of action involves binding to ribosomal proteins, but suffer due to poor pharmacological properties (Gaillard et al, 2016 ). The combination of virginiamycin S1 targeting the apicoplast, and apicidin targeting plasmodium orthologs of histone deacetylase, such as PfHDA2 (Darkin-Rattray et al, 1996 ; Coleman et al, 2014 ; Engel et al, 2015 ) suggests that this combination puts pressure on the developmental and growth stages of the parasite.…”

Section: Resultsmentioning

confidence: 99%

Using Machine Learning to Predict Synergistic Antimalarial Compound Combinations With Novel Structures

et al. 2018

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The parasite Plasmodium falciparum is the most lethal species of Plasmodium to cause serious malaria infection in humans, and with resistance developing rapidly novel treatment modalities are currently being sought, one of which being combinations of existing compounds. The discovery of combinations of antimalarial drugs that act synergistically with one another is hence of great importance; however an exhaustive experimental screen of large drug space in a pairwise manner is not an option. In this study we apply our machine learning approach, Combination Synergy Estimation (CoSynE), which can predict novel synergistic drug interactions using only prior experimental combination screening data and knowledge of compound molecular structures, to a dataset of 1,540 antimalarial drug combinations in which 22.2% were synergistic. Cross validation of our model showed that synergistic CoSynE predictions are enriched 2.74 × compared to random selection when both compounds in a predicted combination are known from other combinations among the training data, 2.36 × when only one compound is known from the training data, and 1.5 × for entirely novel combinations. We prospectively validated our model by making predictions for 185 combinations of 23 entirely novel compounds. CoSynE predicted 20 combinations to be synergistic, which was experimentally validated for nine of them (45%), corresponding to an enrichment of 1.70 × compared to random selection from this prospective data set. Such enrichment corresponds to a 41% reduction in experimental effort. Interestingly, we found that pairwise screening of the compounds CoSynE individually predicted to be synergistic would result in an enrichment of 1.36 × compared to random selection, indicating that synergy among compound combinations is not a random event. The nine novel and correctly predicted synergistic compound combinations mainly (where sufficient bioactivity information is available) consist of efflux or transporter inhibitors (such as hydroxyzine), combined with compounds exhibiting antimalarial activity alone (such as sorafenib, apicidin, or dihydroergotamine). However, not all compound synergies could be rationalized easily in this way. Overall, this study highlights the potential for predictive modeling to expedite the discovery of novel drug combinations in fight against antimalarial resistance, while the underlying approach is also generally applicable.

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Section: Resultsmentioning

confidence: 99%

Using Machine Learning to Predict Synergistic Antimalarial Compound Combinations With Novel Structures

et al. 2018

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“…Another antimalarial, atovaquone, also traces its discovery to a plant-derived natural compound [28]. Natural compounds isolated from microorganisms have similarly had a profound impact towards discovery of chemotherapeutic antimalarial agents by providing privileged scaffolds for the synthesis of derivatives including the tetracycline, doxycycline and the lincosamide, clindamycin [30,31].…”

Section: Can Natural Products Prove a Panacea For Transmission-blockimentioning

confidence: 99%

Natural Products: A Potential Source of Malaria Transmission Blocking Drugs?

et al. 2020

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The ability to block human-to-mosquito and mosquito-to-human transmission of Plasmodium parasites is fundamental to accomplish the ambitious goal of malaria elimination. The WHO currently recommends only primaquine as a transmission-blocking drug but its use is severely restricted by toxicity in some populations. New, safe and clinically effective transmission-blocking drugs therefore need to be discovered. While natural products have been extensively investigated for the development of chemotherapeutic antimalarial agents, their potential use as transmission-blocking drugs is comparatively poorly explored. Here, we provide a comprehensive summary of the activities of natural products (and their derivatives) of plant and microbial origins against sexual stages of Plasmodium parasites and the Anopheles mosquito vector. We identify the prevailing challenges and opportunities and suggest how these can be mitigated and/or exploited in an endeavor to expedite transmission-blocking drug discovery efforts from natural products.

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“…It shows both bacteriostatic and bactericidal activities that depend on the concentration and the susceptibility of the target organism. 3 Clarithromycin (CLA) is another 14-membered macrolide, which has largely substituted ERY in the clinical practice. The only 15-membered ring is azithromycin (AZI), which is a derivative that belongs to the macrolide subclass, named azalides.…”

Section: Introductionmentioning

confidence: 99%

Clinical evidences on the antiviral properties of macrolide antibiotics in the COVID-19 era and beyond

Poddighe

Aljofan

2020

Antivir Chem Chemother

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Macrolides are a large group of antibiotics characterised by the presence of a macro-lactone ring of variable size. The prototype of macrolide antibiotics, erythromycin was first produced by Streptomyces and associated species more than half a century ago; other related drugs were developed. These drugs have been shown to have several pharmacological properties: in addition to their antibiotic activity, they possess some anti-inflammatory properties and have been also considered against non-bacterial infections. In this review, we analysed the available clinical evidences regarding the potential anti-viral activity of macrolides, by focusing on erythromycin, clarithromycin and azithromycin. Overall, there is no significant evidences so far that macrolides might have a direct benefit on most of viral infections considered in this review (RSV, Influenza, coronaviruses, Ebola and Zika viruses). However, their clinical benefit cannot be ruled out without further and focused clinical studies. Macrolides may improve the clinical course of viral respiratory infections somehow, at least through indirect mechanisms relying on some and variable anti-inflammatory and/or immunomodulatory effects, in addition to their well-known antibacterial activity.

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Macrolides and associated antibiotics based on similar mechanism of action like lincosamides in malaria

Cited by 36 publications

References 83 publications

Using Machine Learning to Predict Synergistic Antimalarial Compound Combinations With Novel Structures

Using Machine Learning to Predict Synergistic Antimalarial Compound Combinations With Novel Structures

Natural Products: A Potential Source of Malaria Transmission Blocking Drugs?

Clinical evidences on the antiviral properties of macrolide antibiotics in the COVID-19 era and beyond

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