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

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dc.authoridDaemi, Amin/0000-0003-1104-4626
dc.authoridHosseini Hooshiar, Mohammad/0009-0000-4130-6610
dc.contributor.authorYonden, Zafer
dc.contributor.authorReshadi, Samira
dc.contributor.authorHayati, Ahmad Farrokh
dc.contributor.authorHooshiar, Mohammad Hossein
dc.contributor.authorGhasemi, Sholeh
dc.contributor.authorYonden, Hakan
dc.contributor.authorDaemi, Amin
dc.date.accessioned2025-03-17T12:27:46Z
dc.date.available2025-03-17T12:27:46Z
dc.date.issued2025
dc.departmentTarsus Üniversitesi
dc.description.abstractThe 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.
dc.description.sponsorshipThe authors received no specific funding for this work.
dc.description.sponsorshipThe authors have nothing to report.
dc.identifier.doi10.1002/ddr.70066
dc.identifier.issn0272-4391
dc.identifier.issn1098-2299
dc.identifier.issue1
dc.identifier.pmid39932058
dc.identifier.scopus2-s2.0-85218435226
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1002/ddr.70066
dc.identifier.urihttps://hdl.handle.net/20.500.13099/2414
dc.identifier.volume86
dc.identifier.wosWOS:001417380600001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherWiley
dc.relation.ispartofDrug Development Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250316
dc.subjectAI-designed antibiotics
dc.subjectantibiotic resistance
dc.subjectdrug-resistant bacteria
dc.subjectmechanism of action
dc.subjectnovel drug discovery
dc.subjectsuperbugs
dc.titleReviewing on AI-Designed Antibiotic Targeting Drug-Resistant Superbugs by Emphasizing Mechanisms of Action
dc.typeArticle

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