Riboswitches are RNA molecules that regulate gene expression by sensing metabolites, presenting an interesting target for synthetic biology applications. We present a computational approach based on ViennaRNA tools to dissect and model RNA-ligand interaction dynamics under kinetic control, enabling simulation of riboswitch folding
In the world of synthetic biology, the design of RNA switches holds immense promise for various applications, ranging from diagnostics to therapeutics. This paper presents a comprehensive workflow for designing RNA switches that can dynamically alter their structural conformations in response to specific ligands
In the realm of gene regulation, understanding the precise mechanisms by which RNA molecules fold and function during transcription is crucial. This study delves into this intricate process, focusing on the type I-A 2′-deoxyguanosine (2'dG)-sensing riboswitch from Mesoplasma florum. By employing NMR spectroscopy and computational modeling, we have uncovered critical insights into how co-transcriptional folding influences ligand binding and conformational switching in these regulatory RNAs.
Discrete energy landscapes provide a valuable means for analyzing non-equilibrium properties of biopolymers. In this study we propose a memory-efficient approach for local flooding of the lower portion of an RNA folding landscape
In this paper, we introduce a novel approach to exploring the energy landscapes of discrete polymer models, with a particular emphasis on the lower-energy regions that play a critical role in understanding biopolymer folding behavior