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.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
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Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson· International Conference on...· 44 citations· ⚡5
It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...
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.