Nuclera’s eProtein Discovery™ benchtop system speeds up protein expression and purification workflows in research labs, automating construct screening to inform protein scale-up in under 48 hours. Partnering with Google Cloud, Nuclera has integrated AlphaFold2 into its software, which makes it easier to access structural predictions. Direct access to AlphaFold2 results in enhanced construct quality with an in silico filter during experiment design, increasing the likelihood of identifying optimal target proteins for discovery programs.

Full-length protein expression often results in inclusion bodies, non-expression, or aggregation. To maximize yield and solubility, exploring variants of different lengths is effective. Alphafold2 can aid in the rational design of protein constructs by identifying and eliminating flexible, disordered, or aggregation-prone regions in the predicted structure.

This feature will be available to our existing customers in Q3 2024 and available publicly by Q4 2024

The length to fold a structure depends on the size of the protein ie. the number of residues it has. As an indication, if the size is about 1000 residues, you can obtain the predicted folded protein structure in about 3 hours. In the eProtein Cloud Software this prediction happens in the background and alerts you when the structure is ready for you to work with.

The eProtein Discovery system was designed to allow scientists to screen multiple options (construct variations, solubility tags and cell-free expression conditions) simulaneously to increase the chance of finding a viable option for their target on the same cartridge. Solubility tags are recognized for their ability to improve protein solubility and stability. These tags vary in size and properties, offering a range of options for researchers. In addition to solubility tags, additives in cell-free blends can also be explored. Strategies such as incorporating chaperones, creating oxidizing environments, or supplementing expression mixes with cofactors and metal ions are viable approaches to increase both yield and the proportion of soluble proteins.

Another aspect of our screening involves solubility tags. We offer a selection of seven different solubility tags alongside your target protein, which helps address challenging proteins. For instance, when folding these structures with your target protein or its variant fused with a solubility tag, such as a classic fusion protein, we observe that the solubility tags fold effectively on their own due to their well-characterized structures available in databases like PDB. This separation is facilitated by a linker that prevents significant interaction between the tag and the target protein. Our implementation of AlphaFold2 has shown that it predicts these structures reliably.

Our technology enables highly efficient reaction miniaturization, significantly reducing the amount of DNA required. This is the first benefit. As part of our product line-up, once you've designed your DNA constructs using our software, we offer a convenient service allowing you to place orders directly with our preferred DNA vendor. Currently, we utilize linear DNA for our expression templates and have successfully tested our technology with plasmids.

The innovation brought by predictive models like AlphaFold2 is transformative for downstream processes in biotechnology and pharmaceuticals. By accurately predicting protein structures, AlphaFold2 streamlines protein engineering, drug discovery, and bioprocessing. Researchers can design proteins with specific functions or optimize existing ones more efficiently. This precision reduces trial and error in protein production, enhances protein stability and solubility, and enables the design of novel therapeutics with better efficacy and fewer side effects. Ultimately, AlphaFold2 accelerates the development of new drugs and biotechnological products, making the entire process more cost-effective and sustainable.