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"Antibiotics Development."
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Persisters—as elusive as ever
Persisters—a drug-tolerant sub-population in an isogenic bacterial culture—have been featured throughout the last decade due to their important role in recurrent bacterial infections. Numerous investigations detail the mechanisms responsible for the formation of persisters and suggest exciting strategies for their eradication. In this review, we argue that the very term “persistence” is currently used to describe a large and heterogeneous set of physiological phenomena that are functions of bacterial species, strains, growth conditions, and antibiotics used in the experiments. We caution against the oversimplification of the mechanisms of persistence and urge for a more rigorous validation of the applicability of these mechanisms in each case.
Journal Article
Artificial Intelligence and Antibiotic Discovery
Over recent decades, a new antibiotic crisis has been unfolding due to a decreased research in this domain, a low return of investment for the companies that developed the drug, a lengthy and difficult research process, a low success rate for candidate molecules, an increased use of antibiotics in farms and an overall inappropriate use of antibiotics. This has led to a series of pathogens developing antibiotic resistance, which poses severe threats to public health systems while also driving up the costs of hospitalization and treatment. Moreover, without proper action and collaboration between academic and health institutions, a catastrophic trend might develop, with the possibility of returning to a pre-antibiotic era. Nevertheless, new emerging AI-based technologies have started to enter the field of antibiotic and drug development, offering a new perspective to an ever-growing problem. Cheaper and faster research can be achieved through algorithms that identify hit compounds, thereby further accelerating the development of new antibiotics, which represents a vital step in solving the current antibiotic crisis. The aim of this review is to provide an extended overview of the current artificial intelligence-based technologies that are used for antibiotic discovery, together with their technological and economic impact on the industrial sector.
Journal Article
Biogenic Synthesis and Characterisation of Novel Potassium Nanoparticles by Capparis spinosa Flower Extract and Evaluation of Their Potential Antibacterial, Anti-biofilm and Antibiotic Development
Scientific researches on the synthesis, characterisation, and biological activity of potassium nanoparticles (K NPs) are extremely rare. In our study, we successfully synthesised a novel form of K NPs using
Capparis spinosa
(
C. spinosa
) flower extract as a reducing and capping agent. The formation of K NPs in new form (K
2
O NPs) was confirmed by UV–vis and XRD spectra. Furthermore, the FTIR results indicated the presence of specific active biomolecules in the
C. spinosa
extract which played a crucial role in reducing and stabilising K
2
O NPs. SEM imaging demonstrated that the K
2
O NPs exhibited irregular shapes with nanosizes ranging between 25 and 95 nm. Remarkably, the biosynthesised K
2
O NPs displayed considerable antibacterial activity against a wide range of multidrug-resistant (MDR) pathogenic bacteria. K
2
O NPs demonstrated considerable anti-biofilm activity against preformed biofilms produced by MDR bacteria. Combining K
2
O NPs with conventional antibiotics greatly improved their efficacy in compacting the MDR bacterial strains. Industrially, bulk form of potassium oxides was commonly used in the preparation of various antimicrobial compounds such as detergents, bleach, and oxidising solutions. The synthesis of potassium oxide in nanoform has shown remarkable biological efficacy, making it a promising therapeutic approach for pharmaceutical and medical applications.
Journal Article
A small-molecule inhibitor of BamA impervious to efflux and the outer membrane permeability barrier
The development of new antimicrobial drugs is a priority to combat the increasing spread of multidrug-resistant bacteria. This development is especially problematic in gram-negative bacteria due to the outer membrane (OM) permeability barrier and multidrug efflux pumps. Therefore, we screened for compounds that target essential, nonredundant, surface-exposed processes in gram-negative bacteria. We identified a compound, MRL-494, that inhibits assembly of OM proteins (OMPs) by the β-barrel assembly machine (BAM complex). The BAM complex contains one essential surface-exposed protein, BamA. We constructed a bamA mutagenesis library, screened for resistance to MRL-494, and identified the mutation bamAE470K
. BamAE470K restores OMP biogenesis in the presence of MRL-494. The mutant protein has both altered conformation and activity, suggesting it could either inhibit MRL-494 binding or allow BamA to function in the presence of MRL-494. By cellular thermal shift assay (CETSA), we determined that MRL-494 stabilizes BamA and BamAE470K from thermally induced aggregation, indicating direct or proximal binding to both BamA and BamAE470K. Thus, it is the altered activity of BamAE470K responsible for resistance to MRL-494. Strikingly, MRL-494 possesses a second mechanism of action that kills gram-positive organisms. In microbes lacking an OM, MRL-494 lethally disrupts the cytoplasmic membrane. We suggest that the compound cannot disrupt the cytoplasmic membrane of gram-negative bacteria because it cannot penetrate the OM. Instead, MRL-494 inhibits OMP biogenesis from outside the OM by targeting BamA. The identification of a small molecule that inhibits OMP biogenesis at the cell surface represents a distinct class of antibacterial agents.
Journal Article
Antibiotic Resistance
Years of using, misusing, and overusing antibiotics and other antimicrobial drugs has led to the emergence of multidrug-resistant 'superbugs.' The IOM's Forum on Microbial Threats held a public workshop April 6-7 to discuss the nature and sources of drug-resistant pathogens, the implications for global health, and the strategies to lessen the current and future impact of these superbugs.
eBook
White Paper: Developing Antimicrobial Drugs for Resistant Pathogens, Narrow-Spectrum Indications, and Unmet Needs
Despite progress in antimicrobial drug development, a critical need persists for new, feasible pathways to develop antibacterial agents to treat people infected with drug-resistant bacteria. Infections due to resistant gram-negative bacilli continue to cause unacceptable morbidity and mortality rates. Antibacterial agents have been historically studied in noninferiority clinical trials that focus on a single site of infection (eg, complicated urinary tract infections, intra-abdominal infections), yet these designs may not be optimal, and often are not feasible, for study of infections caused by drug-resistant bacteria. Over the past several years, multiple stakeholders have worked to develop consensus regarding paths forward with a goal of facilitating timely conduct of antimicrobial development. Here we advocate for a novel and pragmatic approach and, toward this end, present feasible trial designs for antibacterial agents that could enable conduct of narrow-spectrum, organism-specific clinical trials and ultimately approval of critically needed new antibacterial agents.
Journal Article
Deep Learning and Antibiotic Resistance
Antibiotic resistance (AR) is a naturally occurring phenomenon with the capacity to render useless all known antibiotics in the fight against bacterial infections. Although bacterial resistance appeared before any human life form, this process has accelerated in the past years. Important causes of AR in modern times could be the over-prescription of antibiotics, the presence of faulty infection-prevention strategies, pollution in overcrowded areas, or the use of antibiotics in agriculture and farming, together with a decreased interest from the pharmaceutical industry in researching and testing new antibiotics. The last cause is primarily due to the high costs of developing antibiotics. The aim of the present review is to highlight the techniques that are being developed for the identification of new antibiotics to assist this lengthy process, using artificial intelligence (AI). AI can shorten the preclinical phase by rapidly generating many substances based on algorithms created by machine learning (ML) through techniques such as neural networks (NN) or deep learning (DL). Recently, a text mining system that incorporates DL algorithms was used to help and speed up the data curation process. Moreover, new and old methods are being used to identify new antibiotics, such as the combination of quantitative structure-activity relationship (QSAR) methods with ML or Raman spectroscopy and MALDI-TOF MS combined with NN, offering faster and easier interpretation of results. Thus, AI techniques are important additional tools for researchers and clinicians in the race for new methods of overcoming bacterial resistance.
Journal Article
Road to clinical efficacy: challenges and novel strategies for antimicrobial peptide development
Since the discovery of magainins, cecropins and defensins 30 years ago, antimicrobial peptides (AMPs) have been hailed as a potential solution to the dearth of novel antibiotic development. AMPs have shown robust activity against a wide variety of pathogens, including drug-resistant bacteria. Unlike small-molecule antibiotics, however, AMPs have failed to translate this success to the clinic. Only the polymyxins, gramicidins, nisin and daptomycin are currently approved for medical use; the latter is the only example to have been developed in the last several decades. Nonetheless, researchers continue to isolate, modify and develop novel AMPs for therapeutic applications. Efforts have focused on increasing stability, reducing cytotoxicity, improving antimicrobial activity and incorporating AMPs in novel formulations, including nanoscale particles. As peptide synthesis and recombinant production methodologies improve, and more relevant bioassays become available, it becomes increasingly likely that AMPs will break the regulatory barrier and enter the marketplace as valuable antimicrobial weapons in the next 10 years.
Journal Article
Efficient Delivery of Investigational Antibacterial Agents via Sustainable Clinical Trial Networks
The economics of antibiotics can be improved by infectious diseases-specific clinical trial networks. While developers would still need to implement an independent phase 1 program as well as studies focused on highly resistant pathogens, standardized procedures in a network focused on usual drug resistance phenotype isolates would permit sharing of controls and would predictably generate high-quality pivotal data for product registration while creating cost and time savings in the range of 30%–40%. This would reduce economic barriers to antibiotic development and contribute to public health.
Journal Article