期刊
BIOPOLYMERS
卷 112, 期 4, 页码 -出版社
WILEY
DOI: 10.1002/bip.23415
关键词
DNA structure; FRET-melting; G-quadruplex; G-quartet; UV-melting
资金
- Centre National de la Recherche Scientifique
- Ecole Polytechnique, Universite Paris-Saclay
- Institut Curie
- Institut National de la Sante et de la Recherche Medicale
The article introduces a study on characterizing G-quadruplex structures in batches using the FRET-melting assay and proposes the FRET-MC (melting competition) method, which has been validated through extensive experiments for the accuracy and reliability of detecting G4 structures.
G-quadruplexes (G4) play crucial roles in biology, analytical chemistry and nanotechnology. The stability of G4 structures is impacted by the number of G-quartets, the length and positions of loops, flanking motifs, as well as additional structural elements such as bulges, capping base pairs, or triads. Algorithms such as G4Hunter or Quadparser may predict if a given sequence is G4-prone by calculating a quadruplex propensity score; however, experimental validation is still required. We previously demonstrated that this validation is not always straightforward, and that a combination of techniques is often required to unambiguously establish whether a sequence forms a G-quadruplex or not. In this article, we adapted the well-known FRET-melting assay to characterize G4 in batch, where the sequence to be tested is added, as an unlabeled competitor, to a system composed of a dual-labeled probe (F21T) and a specific quadruplex ligand. PhenDC3 was preferred over TMPyP4 because of its better selectivity for G-quadruplexes. In this so-called FRET-MC (melting competition) assay, G4-forming competitors lead to a marked decrease of the ligand-induced stabilization effect (Delta T-m), while non-specific competitors (e.g., single- or double-stranded sequences) have little effect. Sixty-five known sequences with different typical secondary structures were used to validate the assay, which was subsequently employed to assess eight novel sequences that were not previously characterized.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据