
Present-day rational drug design approaches are based on exploiting unique features of the target biomolecules, small- or macromolecule drug candidates and physical forces that govern their interactions. The 2013 Nobel Prize in chemistry awarded 'for the development of multiscale models for complex chemical systems' once again demonstrated the importance of the tailored drug discovery that reduces the role of the trial-and-error approach to a minimum. The intentional dissemination of Bacillus anthracis spores in 2001 via the so-called anthrax letters has led to increased efforts, politically and scientifically, to develop medical countermeasures that will protect people from the threat of anthrax bioterrorism.This article provides an overview of the recent rational drug design approaches for discovering inhibitors of anthrax toxin. The review also directs the readers to the vast literature on the recognized advances and future possibilities in the field.Existing options to combat anthrax toxin lethality are limited. With the only anthrax toxin inhibiting therapy (protective antigen-targeting with a monoclonal antibody, raxibacumab) approved to treat inhalational anthrax, the situation, in our view, is still insecure. Further, the FDA's animal rule for drug approval, which clears compounds without validated efficacy studies on humans, creates a high level of uncertainty, especially when a well-characterized animal model does not exist. Better identification and validation of anthrax toxin therapeutic targets at the molecular level as well as elucidation of the parameters determining the corresponding therapeutic windows are still necessary for more effective therapeutic options.
Antigens, Bacterial, Bacillus anthracis, Drug Design, Bacterial Toxins, Animals, Humans, Antitoxins
Antigens, Bacterial, Bacillus anthracis, Drug Design, Bacterial Toxins, Animals, Humans, Antitoxins
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 33 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
