Targeting bacterial transcription factors for infection control: opportunities and challenges.

Artificial Intelligence Transcription factor antibiotic resistance bacterial pathogenesis drug design infection control

Journal

Transcription
ISSN: 2154-1272
Titre abrégé: Transcription
Pays: United States
ID NLM: 101530967

Informations de publication

Date de publication:
21 Dec 2023
Historique:
medline: 21 12 2023
pubmed: 21 12 2023
entrez: 21 12 2023
Statut: aheadofprint

Résumé

The rising threat of antibiotic resistance in pathogenic bacteria emphasizes the need for new therapeutic strategies. This review focuses on bacterial transcription factors (TFs), which play crucial roles in bacterial pathogenesis. We discuss the regulatory roles of these factors through examples, and we outline potential therapeutic strategies targeting bacterial TFs. Specifically, we discuss the use of small molecules to interfere with TF function and the development of transcription factor decoys, oligonucleotides that compete with promoters for TF binding. We also cover peptides that target the interaction between the bacterial TF and other factors, such as RNA polymerase, and the targeting of sigma factors. These strategies, while promising, come with challenges, from identifying targets to designing interventions, managing side effects, and accounting for changing bacterial resistance patterns. We also delve into how Artificial Intelligence contributes to these efforts and how it may be exploited in the future, and we touch on the roles of multidisciplinary collaboration and policy to advance this research domain.

Identifiants

pubmed: 38126125
doi: 10.1080/21541264.2023.2293523
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-28

Auteurs

Ahmed Al-Tohamy (A)

Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA.
Department of Cell Biology, Biotechnology Research Institute, National Research Centre, Cairo, Egypt.

Anne Grove (A)

Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA.

Classifications MeSH