Microbial-inspired antidotes to repurpose toxic compounds as antibiotics
Samad, T. S.; Ngambenjawong, C.; Ko, H.; Patel, S.; DeAgazio, C.; Fleming, H. E.; Bhatia, S. N.
Show abstract
Antibiotic-resistant (AMR) bacterial infections are a major global health threat. Despite the critical need for new antimicrobials, progress is constrained by protracted development timelines, as well as the requirement for chemical novelty to avoid cross-resistance. Although advances in high-throughput screening, genome mining, and machine learning have greatly accelerated antimicrobial discovery, insufficient separation between antibacterial efficacy and host toxicity remains a bottleneck, precluding the clinical development of many promising compounds. Here, we establish a generalizable, two-component strategy to engineer antimicrobial safety and mobilize otherwise inaccessible chemical space for antimicrobial therapy, using calicheamicin, a potent cytotoxin with unacceptable host toxicity, as a proof of concept. In the first arm, we engineer a conditionally-active drug conjugate that limits calicheamicin activity to infected tissue, thereby reducing systemic toxicity. In the second arm, we co-administer a re-engineered self-resistance enzyme from Micromonospora echinospora, the natural producer of calicheamicin, as an "antidote" to neutralize calicheamicin present outside of infected tissue, further mitigating off-target toxicity. The conditionally-active conjugate exhibits activity against Gram-negative and Gram-positive pathogens in response to a protease present within the infected microenvironment. When delivered in combination with the antidote, antibacterial efficacy is maintained while off-target toxicity is reduced in mouse models of Gram positive and negative bacterial pneumonia. We anticipate that our dual strategy, which engineers, rather than selects for enhanced drug safety, by combining conditional drug activity with antidote-driven neutralization of off-target effects, provides a generalizable framework for mobilizing other promising but toxic compounds as antimicrobials.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.