Protein design for new-to-nature chemistries This project is funded by VR and Novo Nordisk Foundation individual grants to Per-Olof Syrén as well as by SSF, MISTRA, FORMAS. This multicentre project will use de novo enzyme design to bridge transition-metal catalysis with protein chemistry for the generation of new-to-nature enzymatic reactions. Enzymes offer a powerful route towards sustainable synthesis by enabling highly selective transformations under mild conditions, including from complex renewable feedstocks such as biomass. However, natural enzymes are lacking for many industrially important reactions. This limitation is especially clear for carbon–carbon and carbon–heteroatom bond formation, which is central to the synthesis of platform chemicals, materials, agrochemicals and pharmaceuticals, but still commonly relies on petroleum-based feedstocks, hazardous reagents, organic solvents and energy-intensive conditions. Here, we will create artificial metalloenzymes de novo for carbon–carbon bond-forming reactions with broad catalytic scope, with an initial focus on cross-coupling-type chemistry. Our computational pipeline combines quantum mechanics, molecular dynamics and generative AI-based protein design. First, high-level QM calculations will be used to define transition states, intermediates and metal-coordination geometries for the target reactions. Second, generative AI will be used to design protein backbones capable of harboring these catalytic motifs, including the required metal centre, reaction intermediates and catalytic amino acids. Third, the resulting designs will be validated using AlphaFold-type structure prediction, docking and molecular dynamics to assess foldability, active-site preorganisation, substrate binding and suitability of the catalytic geometry. Promising designs will be tested experimentally and further optimized by focused mutagenesis and directed evolution. The project builds on strong progress and support from previous PDC/NAISS-supported work, where we have modelled enzyme mechanisms and unraveled new chemistries in existing biocatalysts, including metalloenzymes and biocatalysts for plastic degradation. Resources from the most recent project NAISS 2025/5-398 have already contributed to two published papers, one preprint and two manuscripts under review in Nature Communications and ACS Catalysis. This demonstrates both the productivity of the allocation and the feasibility of the proposed computational–experimental workflow. The project requires multicentre usage because different parts of the workflow have distinct computational demands. Dardel is essential for CPU-intensive QM and US-GAMESS calculations on large models of complex metalloenzymes and transition-metal-containing active sites. Arrhenius is essential for GPU-intensive molecular dynamics using OpenMM, generative AI-based protein design, AlphaFold-based validation and docking workflows, including Schrödinger calculations. By implementing new mechanisms in designed metalloenzymes guided by high-level simulations and experimental data, this project will generate designer enzymes capable of catalyzing transformations of high industrial and societal relevance that are currently inaccessible to biocatalysis. The long-term outcome will be a general platform for sustainable protein-based catalysis for green chemistry applications. Ca 4 people from Syrén’s group will use these resources