Strategies to Improve the Potency of Oxazolidinones towards Bacterial Biofilms

In Vitro Activities of Oxazolidinone Antibiotics Alone and in Combination with C-TEMPO against Methicillin-Resistant Staphylococcus aureus Biofilms

Infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are a global health concern. The propensity of MRSA to form biofilms is a significant contributor to its pathogenicity. Strategies to treat biofilms often involve small molecules that disperse the biofilm into planktonic cells. Linezolid and, by extension, theoxazolidinones have been developed to treat infections caused by Gram-positive bacteria such as MRSA. However, the clinical development of these antibiotics has mainly assessed the susceptibility of planktonic cells to the drug. Previous studies evaluating the anti-biofilm activity of theoxazolidinones have mainly focused on the biofilm inhibition of Enterococcus faecalis and methicillin-sensitive Staphylococcus aureus, with only a few studies investigating the activity of oxazolidinones for eradicating established biofilms for these species. Very little is known about the ability of oxazolidinones to eradicate MRSA biofilms. In this work, five oxazolidinones were assessed against MRSA biofilms using a minimum biofilm eradication concentration (MBEC) assay. All oxazolidinones had inherent antibiofilm activity. However, only ranbezolid could completely eradicate MRSA biofilms at clinically relevant concentrations. The susceptibility of the MRSA biofilms to ranbezolid was synergistically enhanced by coadministration with the nitroxide biofilm dispersal agent C-TEMPO. We presume that ranbezolid acts as a dual warhead drug, which combines the mechanism of action of the oxazolidinones with a nitric oxide donor or cytotoxic drug.

Oxazolidinones as versatile scaffolds in medicinal chemistry

Oxazolidinone is a five-member heterocyclic ring with several biological applications in medicinal chemistry. Among the three possible isomers, 2-oxazolidinone is the most investigated in drug discovery. Linezolid was pioneered as the first approved drug containing an oxazolidinone ring as the pharmacophore group. Numerous analogues have been developed since its arrival on the market in 2000. Some have succeeded in reaching the advanced stages of clinical studies. However, most oxazolidinone derivatives reported in recent decades have not reached the initial stages of drug development, despite their promising pharmacological applications in a variety of therapeutic areas, including antibacterial, antituberculosis, anticancer, anti-inflammatory, neurologic, and metabolic diseases, among other areas. Therefore, this review article aims to compile the efforts of medicinal chemists who have explored this scaffold over the past decades and highlight the potential of the class for medicinal chemistry.

Advances in computational frameworks in the fight against TB: The way forward

Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its "End TB" strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for-early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.