| Literature DB >> 31022923 |
Bernardo Ribeiro da Cunha1, Luís P Fonseca2, Cecília R C Calado3.
Abstract
Given the increase in antibiotic-resistant bacteria, alongside the alarmingly low rate of newly approved antibiotics for clinical usage, we are on the verge of not having effective treatments for many common infectious diseases. Historically, antibiotic discovery has been crucial in outpacing resistance and success is closely related to systematic procedures-platforms-that have catalyzed the antibiotic golden age, namely the Waksman platform, followed by the platforms of semi-synthesis and fully synthetic antibiotics. Said platforms resulted in the major antibiotic classes: aminoglycosides, amphenicols, ansamycins, beta-lactams, lipopeptides, diaminopyrimidines, fosfomycins, imidazoles, macrolides, oxazolidinones, streptogramins, polymyxins, sulphonamides, glycopeptides, quinolones and tetracyclines. During the genomics era came the target-based platform, mostly considered a failure due to limitations in translating drugs to the clinic. Therefore, cell-based platforms were re-instituted, and are still of the utmost importance in the fight against infectious diseases. Although the antibiotic pipeline is still lackluster, especially of new classes and novel mechanisms of action, in the post-genomic era, there is an increasingly large set of information available on microbial metabolism. The translation of such knowledge into novel platforms will hopefully result in the discovery of new and better therapeutics, which can sway the war on infectious diseases back in our favor.Entities:
Keywords: antibiotic discovery platforms; drug screening; fully synthetic antibiotics; genomics; lipidomics; metabolomics; metagenomics; proteomics; semi-synthesis
Year: 2019 PMID: 31022923 PMCID: PMC6627412 DOI: 10.3390/antibiotics8020045
Source DB: PubMed Journal: Antibiotics (Basel) ISSN: 2079-6382
Figure 1Evolution of the total antibiotic pipeline and the antibiotic pipeline by stage of development, which includes: Clinical Trials ranging from Phase I, to evaluate safety; Phase II, to access effectiveness and safety; Phase III, to gather statistically significant data on safety, effectiveness and benefits-versus-risk; submission of a New Drug Application, for marketing approval; and lastly, Phase IV for post-marketing surveillance.
Beta-lactam subclasses highlighting their diversity with examples of marketed antibiotics.
| Subclasses | Examples of Marketed Antibiotics |
|---|---|
| Penicillins | Penicillin G, Penicillin V, Ampicillin, Amoxicillin, Bacampicillin, Cloxacillinm, Floxacillin, Mezlocillin, Nafcillin, Oxacillin, Methicillin a, Dicloxacillin a, Carbenicillin b, Idanyl b, Piperacillin b, Ticarcillin b |
| Cephalosporins | Cefalothin c, Cephradinea c, Cefadroxyl c, Cefazolin c, Cephalexin c, Cefuroxine d, Cefaclor d, Cefotetam d, Cefmetazole d, Cefonicid d, Cefixime e, Ceftibuten e, Cefizoxime e, Ceftriaxone e, Cefamandol e, Cefoperazone e, Cefotaxime e, Proxetil e, Cefprozil e, Ceftazidime e, Cefuroxime Axetil e, Cefpodexime e, Cefepime f, Ceftobiprole g |
| Other Minor Subclasses | Flomoxef h, Latamoxef h, Cefoxitin i, Loracarbef j, Imipenem j, Meropenem j, Panipenem j, Aztreonam k, Carumonam k |
a Penicillinase-resistant penicillin; b Anti-pseudomonal penicillin; c First-generation cephalosporin; d Second-generation cephalosporin; e Third-generation cephalosporin; f Fourth-generation cephalosporin; g Fifth-generation cephalosporin; h Oxycepham; i Cefam; j Carbapenem; k Monobactam.
Figure 2Evolution of cephalosporin characteristics over semi-synthetic generations. Because each generation is the result of adding different molecular groups to 7-ACA, characteristics are not necessarily inherited by succeeding generations. For instance, second-generation cephalosporins had reduced potency against Gram-positive pathogens, despite their otherwise improved properties.
Figure 3Schematic representation of the target-based antibiotic discovery platform: potential targets are identified from the genome sequence of pathogens and the host, the products of genes exclusive and essential for bacteria are incorporated into high-throughput screening assays, which identify drug candidates suitable for lead optimization and preclinical development. The latter falls outside the scope of antibiotic discovery, thus it is not discussed.
Figure 4Schematic representation of the cell-based antibiotic discovery platform: drug candidates are identified from cell-based screening assays, a counter-screen excludes cytotoxic compounds, and subsequently genomics tools are applied to identify MOA. Although MOA is not a requisite, it may facilitate lead optimization and preclinical development, for instance, structural information on the target can enable a rational modification of the drug candidate.