Your browser doesn't support javascript.
loading
A Computational Approach for Designing Synthetic Riboswitches for Next-Generation RNA Therapeutics.
Mukherjee, Sumit; Mukherjee, Sunanda Biswas; Barash, Danny.
Afiliação
  • Mukherjee S; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, USA. sumit.mukherjee@nih.gov.
  • Mukherjee SB; Department of Computer Science, Ben-Gurion University, Beer-Sheva, Israel. sumit.mukherjee@nih.gov.
  • Barash D; Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel.
Methods Mol Biol ; 2847: 193-204, 2025.
Article em En | MEDLINE | ID: mdl-39312145
ABSTRACT
Riboswitches are naturally occurring regulatory segments of RNA molecules that modulate gene expression in response to specific ligand binding. They serve as a molecular 'switch' that controls the RNA's structure and function, typically influencing the synthesis of proteins. Riboswitches are unique because they directly interact with metabolites without the need for proteins, making them attractive tools in synthetic biology and RNA-based therapeutics. In synthetic biology, riboswitches are harnessed to create biosensors and genetic circuits. Their ability to respond to specific molecular signals allows for the design of precise control mechanisms in genetic engineering. This specificity is particularly useful in therapeutic applications, where riboswitches can be synthetically designed to respond to disease-specific metabolites, thereby enabling targeted drug delivery or gene therapy. Advancements in designing synthetic riboswitches for RNA-based therapeutics hinge on sophisticated computational techniques, which are described in this chapter. The chapter concludes by underscoring the potential of computational strategies in revolutionizing the design and application of synthetic riboswitches, paving the way for advanced RNA-based therapeutic solutions.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia Computacional / Riboswitch / Biologia Sintética Limite: Humans Idioma: En Revista: Methods Mol Biol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2025 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia Computacional / Riboswitch / Biologia Sintética Limite: Humans Idioma: En Revista: Methods Mol Biol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2025 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos