Our particle-based method allows us to synthesise high complexity peptide arrays by combinatorial synthesis and for an unrivalled prize. We plan to further develop this new technology up to the level of robust prototype machines, and mate it to bioinformatics and readout tools. Together, our procedure(s) should boost the field of proteomics in a similar way as the lithographic technologies did with the field of genomics. Central to our novel method are the activated chemical building blocks that are “frozen” within solid amino acid particles. Thereby, we can use a colour laser printer to send them to defined addresses on a 2D support, where the particles are simply melted to induce a spatially defined coupling reaction of now freed amino acid derivatives. By repeated printing and melting cycles this simple trick yields high complexity peptide arrays. Based on existing pre-prototypes, we will develop a user-friendly peptide laser printer that spatially defined addresses our 20 different amino acid toners in high resolution to a support (WP1), and a scanner that especially fast and sensitive reads out the large formats delivered by the peptide laser printer (WP2). The increased production of amino acid toners and array supports are other bottlenecks in the output of peptide arrays that are tackled in WP3. This should allow us to increase the output of individual peptide spots from currently 0,5 Million to >10 Million peptides per month. Finally, to foster a market for high complexity peptide arrays, we will work out paradigmatic application examples in WP4. These aim to directly screen for antibiotic or apoptosis inducing D-peptides, and for the comprehensive readout of the different antibodies that patrol the serum of autoimmune patients. Based on user-friendly prototype machines, on first paradigmatic application examples for high complexity peptide arrays, and shielded by a strong patent, the participating SMEs will commercialise this new technology.
Chirality is a key factor in the efficacy of many drugs and the production of single enantiomers of chiral intermediates has therefore become increasingly important. Biocatalysis offers high enantioselectivity and regioselectivity in chiral synthesis through enzyme-catalyzed reactions and thus has an important advantage over chemical synthesis. Molecular genomic data is an unprecedented resource of enzymes for biocatalysis, but rational and effective methodologies must be established to realize the full potential of these resources. This project will focus on the discovery of novel enzymes, from both public and proprietary eubacterial genomes, in particular novel alcohol dehydrogenases, cytochrome P450 monooxygenases and amino acid modifying enzymes for use in established and innovative processes for chiral synthesis.
The DataGenome project extends from genome analysis, through cloning, expression, enzyme production, screening and protein engineering, to the enzymatic production of chiral biomolecules. The design of the project takes advantage of broad funnel-approach starting with innovative data-mining and processing of a large number of genes to ensure high flow-through in the process and rational selection of best enzyme candidates. The specific combination of expertise and design of the research project is aimed at high success-rate for the development of successful biocatalysts. Emphasis will be put on effective bioinformatics analysis to minimize the requirement for the more laborious “wet chemistry” analysis as well as development of optimized vector-host systems for efficient gene expression and enzyme production. Rational protein engineering or directed molecular evolution will be employed in order to obtain more robust variants, new substrate preferences or enhanced enantiomeric selectivity. Selected enzymes will be tested in existing and/or novel biocatalytic processes for production of chiral pharmaceutical intermediates with applications in therapeutic areas including AIDS, cancer and Alzheimer’s disease.