Sci Transl MedJClub
From code to cure: Harnessing AI for antibiotic discovery and design.
Science Translational Medicine · · Review
Krishnan, Cao + more
Abstract ↗AI summary
The abstract is read at the publisher; the summary is JClub's.
AI-driven methods now facilitate the exploration of vast chemical and sequence spaces, enabling the design of synthesizable antibiotics with diverse mechanisms.
- Why it matters: Addressing the urgent need for new antibiotics is critical due to rising antimicrobial resistance, and current discovery pipelines are slow and limited.
- What they did: The authors review recent advances in AI for small-molecule and peptide antimicrobials, emphasizing data standards, translational pathways, and regulatory challenges.
- The result: These developments suggest AI can accelerate antibiotic discovery and design, potentially leading to more effective and diverse antimicrobial agents for clinical use.
The findingWhy it mattersWhat they didThe result