Sep 2026· Advancement of science· 0 citations· 48 references
Medicine
TL;DR
A mechanistic framework for the active regulation of SARS-CoV-2 RNA architecture is established and a multilayered host-virus regulatory axis that modulates viral genome heterogeneity is revealed.
Abstract
ABSTRACT The SARS‐CoV‐2 RNA genome functions as a highly structured regulatory scaffold. Although bioinformatic analyses predict widespread RNA G‐quadruplexes (G4s) across the viral genome, their structural diversity and regulatory mechanisms remain poorly understood. Here, we report a diverse landscape of viral G4s encompassing parallel and non‐canonical topologies with remarkable thermostability. Unlike typical eukaryotic G4s, these two‐tetrad viral G4s exhibit a hierarchical ion‐dependent mechanism, in which K+ establishes the core fold, and Mg2 + acts as a secondary regulator promoting conformational compaction. Single‐molecule FRET analysis further distinguishes rigid, long‐lived G4 folds from highly dynamic, metastable species, defining a continuum of conformational states along the viral genome. Functionally, we identify a synergistic yet competitive interplay between the viral nucleocapsid (N) protein and host helicase DDX21. While the N protein acts as a molecular chaperone to promote G4 folding, DDX21 selectively resolves these structures in an ATP‐dependent manner. Strikingly, N and DDX21 jointly constitute a finely tuned, ATP‐driven molecular switch, where ATP availability dictates the equilibrium between G4‐stabilized and resolved states. Our findings establish a mechanistic framework for the active regulation of SARS‐CoV‐2 RNA architecture and reveal a multilayered host–virus regulatory axis that modulates viral genome heterogeneity.
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
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.
D. Graziotin, Xiaofeng Wang, P. Abrahamsson· SSE@SIGSOFT FSE· 56 citations· ⚡4
This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.
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.