Strategies to Counteract Botulinum Neurotoxin A: Nature’s Deadliest Biomolecule
Bibliographic record
Abstract
Conspectus Botulinum neurotoxin serotype A (BoNT/A), marketed commercially as Botox, is the most toxic substance known to man with an estimated intravenous lethal dose (LD 50 ) of 1–2 ng/kg in humans. Despite its widespread use in cosmetic and medicinal applications, no postexposure therapeutics are available for the reversal of intoxication in the event of medical malpractice or bioterrorism. Accordingly, the Centers for Disease Control and Prevention categorizes BoNT/A as a Category A pathogen, posing the highest risk to national security and public health as a result of the ease with which BoNT/A can be weaponized and disseminated. BoNT/A-mediated lethality results from neurons impeded from releasing acetylcholine, which ultimately causes muscle paralysis and possible death by asphyxiation with the loss of diaphragm function. Currently, the only available respite for BoNT/A poisoning is antibody-based therapy; however, this intervention is only effective within 12–24 h postexposure. Small molecule therapeutics remain the only opportunity to reverse BoNT/A intoxication after neuronal poisoning and are urgently needed. Nevertheless, no small molecule BoNT/A inhibitors have reached the clinic or even advanced to clinical trials. This Account highlights the accomplishments and existing challenges facing BoNT/A drug discovery today. Using the comprehensive body of work from our laboratory, we illustrate our nearly two-decade endeavor to discover a clinically relevant BoNT/A inhibitor. Specifically, a discussion on the identification and characterization of new chemical leads, the development of in vitro and in vivo assays, and pertinent discoveries in BoNT/A structural biology related to small molecule inhibition is presented. Lead discovery efforts in our laboratory have leveraged both in vitro high-throughput screening and rational design, and an array of mechanistic strategies for inhibiting BoNT/A has been discovered, including noncovalent inhibition, metal-binding active site inhibition, covalent inhibition, and α- and β-exosite inhibition. We contrast the strengths and weaknesses of each of these mechanistic strategies and propose the most favorable approach for success. Finally, we discuss multiple serendipitous discoveries of antibotulism small molecules with alternative mechanisms of action. Remaining challenges facing clinically relevant BoNT/A inhibition are presented and analyzed, including the current inability to reconcile toxin half-life (months to greater than one year) in neurons with in vivo pharmaceutical lifetimes and reoccurring inconsistencies between in vitro, cellular, and in vivo translation. Our Account of BoNT/A chemical research emphasizes the present accomplishments and critically analyzes the remaining obstacles for drug discovery. Importantly, we call for an increased focus on the discovery of safe and effective covalent inhibitors of BoNT/A that compete with the inherent half-life of the toxin.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".