“Undruggable” proteins without surface-accessible binding sites pose significant challenges to target-based drug discovery. Innovative approaches are needed to tackle these proteins. One promising strategy is targeting them in their nascent chain form at the ribosome, where they have a different conformation than in the folded form. A systematic approach to screen for such compounds has however been lacking. Here, we present a high-throughput assay to identify small molecules that specifically inhibit a protein of interest in its nascent-chain form. The assay employs a human in vitro transcription/translation system and monitors expression of the protein in real time via fluorescence detection. Specific inhibitors for the nascent chain of interest can then be identified by comparison with a counter screen. The assay was optimized to maximal sensitivity and reaction costs of ∼$0.01 per well, enabling large-scale screens. We validated performance with the reference compound PF846 on the nascent chain of the protein PCSK9. Feasibility for high-throughput screening was demonstrated using a library of 1,760 compounds against the oncogenic KRAS variant A146T and the protein ApoC3, with mean Z′ scores of 0.69 and 0.88, respectively. Sixteen global translation inhibitors were identified in each campaign, while no compounds met the criteria for POI-selective inhibition. The assay thus provides a robust platform for larger-scale screening campaigns.
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.