The development of simple, bio-friendly strategies to engineer bright fluorescent proteins (FPs) is crucial for biosensing and bioimaging. Conventional synthesis of FPs requires time-consuming chromophore maturation and tedious preparation, while covalent conjugation methods often involve long reactions and risk loss of bioactivity. Herein, we propose a noncovalent “Dual-Key Lock” strategy and demonstrated the strategy using a selective aggregation-induced emission luminogen (AIEgen), TCBPE. This mechanism relies on the synergistic action of hydrogen bonding and hydrophobic interactions, which collectively confine TCBPE within the binding pocket of bovine serum albumin (BSA@TCBPE), effectively restricting intramolecular motion to activate AIE. Controlled studies with two reference AIEgens (TPE, TCPE) and molecular docking simulations validated this synergistic action with TCBPE. Based on strong noncovalent binding affinity (Kd = 54.8 nM), the fluorescence intensity of BSA@TCBPE reached 92% of its maximum value at 5 min and exhibited 12.62-fold enhancement over free TCBPE. BSA@TCBPE had a high quantum yield of 73.74% and excellent photostability under irradiation at 2 W/cm2 for 90 min. Importantly, the noncovalent conjugation preserved the native functionality of BSA, enabling its effective use in biosensing, while also facilitating high-contrast cellular imaging with low cytotoxicity. This work elucidated key supramolecular interactions and established a simple and efficient platform for constructing high-performance fluorescent proteins with biofunctional applications.
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 sequence constraints.
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.