DNA G-Quadruplex Recognition In Vitro and in Live Cells by a Structure-Specific Nanobody.
Silvia GalliLazaros MelidisSean M FlynnDhaval VarshneyAngela SimeoneJochen SpiegelSarah K MaddenDavid TannahillSamantha KendrickPublished in: Journal of the American Chemical Society (2022)
G-quadruplexes (G4s) are four-stranded DNA secondary structures that occur in the human genome and play key roles in transcription, replication, and genome stability. G4-specific molecular probes are of vital importance to elucidate the structure and function of G4s. The scFv antibody BG4 has been a widely used G4 probe but has various limitations, including relatively poor in vitro expression and the inability to be expressed intracellularly to interrogate G4s in live cells. To address these considerations, we describe herein the development of SG4, a camelid heavy-chain-only derived nanobody that was selected against the human Myc DNA G4 structure. SG4 exhibits low nanomolar affinity for a wide range of folded G4 structures in vitro. We employed AlphaFold combined with molecular dynamics simulations to construct a molecular model for the G4-nanobody interaction. The structural model accurately explains the role of key amino acids and K d measurements of SG4 mutants, including arginine-to-alanine point mutations that dramatically diminish G4 binding affinity. Importantly, predicted amino acid-G4 interactions were subsequently confirmed experimentally by biophysical measurements. We demonstrate that the nanobody can be expressed intracellularly and used to image endogenous G4 structures in live cells. We also use the SG4 protein to positionally map G4s in situ and also on fixed chromatin. SG4 is a valuable, new tool for G4 detection and mapping in cells.
Keyphrases
- induced apoptosis
- amino acid
- cell cycle arrest
- molecular dynamics simulations
- single molecule
- endothelial cells
- high resolution
- transcription factor
- binding protein
- oxidative stress
- gene expression
- circulating tumor
- endoplasmic reticulum stress
- dna damage
- machine learning
- mass spectrometry
- induced pluripotent stem cells
- quantum dots
- sensitive detection
- fluorescence imaging
- label free