Reviewing on AI‐Designed Antibiotic Targeting Drug‐Resistant Superbugs by Emphasizing Mechanisms of Action

抗生素耐药性 抗生素 药物发现 鉴定(生物学) 计算生物学 计算机科学 生化工程 生物 风险分析(工程) 生物技术 医学 生物信息学 工程类 微生物学 植物
作者
Zafer Yönden,Samira Reshadi,Ahmad Farrokh Hayati,Mohammad Hossein Hooshiar,Sholeh Ghasemi,Hakan Yönden,Amin Daemi
出处
期刊:Drug Development Research [Wiley]
卷期号:86 (1): e70066-e70066 被引量:3
标识
DOI:10.1002/ddr.70066
摘要

ABSTRACT The emergence of drug‐resistant bacteria, often referred to as “superbugs,” poses a profound and escalating challenge to global health systems, surpassing the capabilities of traditional antibiotic discovery methods. As resistance mechanisms evolve rapidly, the need for innovative solutions has never been more critical. This review delves into the transformative role of AI‐driven methodologies in antibiotic development, particularly in targeting drug‐resistant bacterial strains (DRSBs), with an emphasis on understanding their mechanisms of action. AI algorithms have revolutionized the antibiotic discovery process by efficiently collecting, analyzing, and modeling complex datasets to predict both the effectiveness of potential antibiotics and the mechanisms of bacterial resistance. These computational advancements enable researchers to identify promising antibiotic candidates with unique mechanisms that effectively bypass conventional resistance pathways. By specifically targeting critical bacterial processes or disrupting essential cellular components, these AI‐designed antibiotics offer robust solutions for combating even the most resilient bacterial strains. The application of AI in antibiotic design represents a paradigm shift, enabling the rapid and precise identification of novel compounds with tailored mechanisms of action. This approach not only accelerates the drug development timeline but also enhances the precision of targeting superbugs, significantly improving therapeutic outcomes. Furthermore, understanding the underlying mechanisms of these AI‐designed antibiotics is crucial for optimizing their clinical efficacy and devising proactive strategies to prevent the emergence of further resistance. AI‐driven antibiotic discovery is poised to play a pivotal role in the global fight against antimicrobial resistance. By leveraging the power of artificial intelligence, researchers are opening new frontiers in the development of effective treatments, ensuring a proactive and sustainable response to the growing threat of drug‐resistant bacteria.
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