Findings establish α-HL electrophysiology as a sensitive platform for distinguishing subtle differences in i-motif conformational stability, with potential applications in DNA secondary structure dynamics and disease-targeted diagnostic strategies.
Abstract
The human c-Myc proto-oncogene is a transcription factor that regulates protein expression and is controlled by GC-rich regulatory sequences capable of adopting non-canonical DNA secondary structures. Here, we use the α-hemolysin (α-HL) protein nanopore to probe pH- and voltage-dependent effects on the stability of the i-motif formed by the 52-nucleotide cytosine-rich c-Myc promoter (c-MycC52). Under acidic conditions, electrophoretically driven c-MycC52 i-motifs are transiently trapped within the α-HL vestibule, generating pH-dependent electrical current signatures that are volumetrically and kinetically distinct and resolvable at the single-molecule level. The larger molecular volume measured in the acidic pH range, compared with that of linearized DNA at neutral pH, is consistent with the formation of an i-motif. In contrast, the applied transmembrane voltage does not induce detectable changes in the topology of the captured i-motif fragments. Kinetic modeling of current fluctuations within a continuous-time Markov chain framework reveals a subtle coupling between the acidic pH-dependent compaction topology of the captured i-motif and its local interactions with the α-HL vestibule interior and constriction zone. Although molar KCl concentrations (1 and 3 M) yield c-MycC52 i-motif structures of comparably similar volumes at low pH, reduced charge screening at lower ionic strength enhances electrostatic repulsion along the negatively charged DNA backbone, rendering the vestibule-captured folded structure kinetically more stable and more effective at occluding the α-HL constriction. These findings establish α-HL electrophysiology as a sensitive platform for distinguishing subtle differences in i-motif conformational stability, with potential applications in DNA secondary structure dynamics and disease-targeted diagnostic strategies.
This work demonstrates that ligand recognition of viral GQ remains preserved within protein condensates and establishes fluorescence spectroscopy as a sensitive approach for resolving hidden binding heterogeneity in GQ-ligand interactions.
Susmita Pradhan, S. M. Tripathi, Shubhangi Sharma et al.· Physical Chemistry, Chemical...· 0 citations
Liquid−liquid phase separation (LLPS) of protein−nucleic acid systems plays a key role in gene expression and regulation, yet the molecular mechanisms governing transcription factor condensation remain poorly understood. Using complementary biophysical techniques, we investigated the ability of TTF1-Helix III, a pept...
Michel W. Jaworek, M. Campanile, Roland Winter et al.· Biomacromolecules· 0 citations
Prokaryotic transcription factors (TFs) lie at the core of antimicrobial resistance, controlling genes that let bacteria survive antibiotic exposure. The AraC/XylS family of TFs is defined by a ∼99-residue DNA-binding domain composed of two helix-turn-helix (HTH) motifs. While this two-motif architecture is considered...
Unlike previously reported G4-selective ligands based on Pd(ii)/Pt(ii) metallacycles, the red box achieves nanomolar affinity and selectivity through a fully metal-free, hydrazone-based scaffold, addressing key limitations related to cost, biodegradability, and long-term biocompatibility.
Paula Novo, Iván Montes de Oca, C. García-Delgado et al.· RSC Chemical Biology· 0 citations
Selective molecular recognition of dynamic nucleic acid structures is fundamental to DNA replication, yet the physical mechanisms by which intrinsically disordered protein domains achieve this selectivity remain poorly understood. Here, we investigate how the intrinsically disordered C-terminal domain (CTD) of the bact...
Lulu Enkhbaatar, P. H. von Hippel, Andrew H. Marcus· bioRxiv· 0 citations
A regulatory role is identified for the conserved, intrinsically disordered C-terminal tails of GroEL, one of the best-studied ATP-dependent chaperones, to reveal how the conformational properties of an intrinsically disordered element can be exploited to optimize the energetic efficiency and functional timing of a lar...
Morgan Powers, Kacie A. Evans, Sun He et al.· bioRxiv· 0 citations
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.