The widespread emergence of antibiotic resistance necessitates the development of novel agents with unique mechanisms of action. Obafluorin (OB), a natural β-lactone antibiotic, is a covalent inhibitor of threonyl-tRNA synthetase (ThrRS), but the high conservation of the active site between prokaryote and eukaryote ThrRSs results in minimal selectivity, hindering the therapeutic potential of OB. Here, we report a structure dynamics-based design strategy that transforms OB into a selective antibacterial agent. OB inhibits human and bacterial ThrRSs with nearly equal potency due to identical binding modes. The nitrophenyl moiety of OB is proposed as a 'kinetic sensor' that discriminates between sensitive and resistant ThrRS paralogs. Guided by this insight, we designed a series of OB analogs through rational modification of this moiety. Among them, OB-D4 bearing a para-methoxyphenyl group in place of the nitrophenyl group, exhibited a 241-fold selectivity for bacterial over human ThrRS, along with a markedly improved safety profile with minimal cytotoxicity. In a murine skin infection model, OB-D4 effectively eradicated pathogens, resolving inflammation, and promoting wound healing. Together, this work establishes a 'kinetic sensor' strategy for achieving species selectivity, turning a fundamental challenge in drug discovery-high active-site conservation-into an exploitable opportunity based on dynamic differences.
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.