The inclusion of non-proteinogenic amino acids (npAAs) into proteins vastly expands their chemical repertoire and hence possible functional diversity. However, it remains challenging to obtain non-proteinogenic sequences that carry out a specific task. Here we develop a platform to discover functional non-standard proteins and illustrate its utility by generating a family of bioactive proteins whose hydrophobic cores are built using fluorinated amino acids (fAAs). Starting from the protein chymotrypsin inhibitor 2 (CI2), we use genetic code reprogramming, combinatorial mutagenesis and mRNA display-based in vitro selection to discover fluorinated mutant sequences with optimised inhibitory activity. Using microwave-assisted solid-phase peptide synthesis, we perform preparative chemical synthesis of 14 selected proteins, which contain up to eight fAAs-or 19 fluorine atoms. All are nanomolar inhibitors of chymotrypsin; several hits are more active than the wildtype, and possess thermostabilities of up to 70°C. Crystal structures reveal that these proteins maintain native-like folds, with fluorine atoms forming close and epistatically coupled packing contacts within the core. This work demonstrates how to generate functional protein sequences with multiple interacting npAAs, namely neoproteins, and thereby provides a framework for exploring the use of unnatural building blocks in protein design.
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.