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

IF 3.5 4区 医学 Q2 CHEMISTRY, MEDICINAL Drug Development Research Pub Date : 2025-02-11 DOI:10.1002/ddr.70066
Zafer Yönden, Samira Reshadi, Ahmad Farrokh Hayati, Mohammad Hossein Hooshiar, Sholeh Ghasemi, Hakan Yönden, Amin Daemi
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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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来源期刊
CiteScore
6.40
自引率
2.60%
发文量
104
审稿时长
6-12 weeks
期刊介绍: Drug Development Research focuses on research topics related to the discovery and development of new therapeutic entities. The journal publishes original research articles on medicinal chemistry, pharmacology, biotechnology and biopharmaceuticals, toxicology, and drug delivery, formulation, and pharmacokinetics. The journal welcomes manuscripts on new compounds and technologies in all areas focused on human therapeutics, as well as global management, health care policy, and regulatory issues involving the drug discovery and development process. In addition to full-length articles, Drug Development Research publishes Brief Reports on important and timely new research findings, as well as in-depth review articles. The journal also features periodic special thematic issues devoted to specific compound classes, new technologies, and broad aspects of drug discovery and development.
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