University of Groningen: Three Horizon Europe MSCA Doctoral Network grants for the Faculty of Science and Engineering
Three researchers of the Faculty of Science and Engineering (FSE) have received a Horizon Europe MSCA Doctoral Network grant. Dr. Sandy Schmidt of the Groningen Research Institute of Pharmacy (GRIP) is coordinator of the BiodeCCodiNNg project. Professor Gerrit J. Poelarends (GRIP) is also involved in this project. Next to that, Poelarends is a partner in the BiocatCodeExpander project. Professor Marco W. Fraaije of the Groningen Biomolecular Sciences and Biotechnology Institute (GBB) is a partner in the project DECADES.
With a Doctoral Network grant (formerly Innovative Training Network), a consortium of universities, research institutes and industrial partners can set up an international training network for training PhD students.
BiodeCCodiNNg | Dr. Sandy Schmidt, coordinator & Prof. Gerrit J. Poelarends (both GRIP)
Dr. Sandy Schmidt is the coordinator and Prof. Gerrit J. Poelarends is a partner in the BiodeCCodiNNg project. They will receive EUR 820,000 of the total grant amount of almost EUR 3 million. The project BiodeCCodiNNg aims to decode novel reaction chemistries from enzymes that are not accessible with the existing biocatalyst portfolio. With this, the researchers intend to build important molecules such as precursors for pharmaceuticals. Expanding the toolbox of available biocatalysts enabling novel reactions not yet accessible with the existing enzymes is a formidable challenge. However, it will open exciting new avenues for applications in the chemical and pharmaceutical industries. The main goal of BiodeCCodiNNg is to train and educate Europe’s next ten visionaries for a sustainable future on cutting-edge enzyme technology. The network is established by experts from European academic institutions and industrial partners.
BiocatCodeExpander | Prof. Gerrit J. Poelarends (GRIP)
Prof. Gerrit J. Poelarends is a partner in the BiocatCodeExpander project. This project receives almost EUR 2.7 million. The aim of the project is to expand the diversity of functional groups present in proteins. With this, the consortium intents to enhance biocatalysis by using non-canonical amino acids (NCAAs) as building blocks for enzyme engineering. This Doctoral Network brings together scientists with different expertise, ranging from synthetic biology to bioorganic chemistry. Together they will train and educate ten PhD students and they aim to ensure the development of efficient methodologies for NCAA incorporation in proteins. The proposed research affords new tools and applications. The newly designed biocatalysts are envisioned to be important for the development of new biotechnological processes for a greener, more environmentally friendly production of chemicals and pharmaceuticals. Poelarends and his team receive around EUR 274,000 to develop novel biocatalysts for new-to-nature C-C bond-forming reactions, which are highly looked-for in pharmaceutical synthesis.
Chemical industries are facing the challenging transition from classic manufacture of petroleum-based chemicals to the sustainable synthesis of bio-based products. This is a complex transition that requires an interdisciplinary approach. Solvents play a crucial role in the chemical industries across the whole production chain and they also account significantly for the environmental impact of reactions. That’s why there is an urgent need for new solvents that can be useful for synthetic processes and that are also environmentally friendly. Deep Eutectic Solvents (DESs) have been appointed as ‘the solvents of the 21st century’. DESs have perfect properties and they offer a new dimension as ‘Safe- and Sustainable-by-Design’ solvents for process intensification in (bio)catalysis. This interdisciplinary Doctoral Network project will therefore focus on these Deep Eutectic Solvents. Leibniz University Hanover is coordinator. One PhD student will be working in Marco Fraaije’s research group. He/she will focus on engineering solvent-tolerant enzymes, using computational structure-based predictions.