Chemical and bio-industries have a steadily growing demand for enzyme biocatalysts, which can catalyze a huge variety of different chemical reactions with high activity, substrate specificity and enantioselectivity. However, enzymes have been evolved by nature to work in living cells
and under mild reaction conditions; consequently, most enzymes cannot be applied in industrial processes directly. Although it is known that few enzymes exist, which are well suited for biotechnological applications, the molecular basis is unknown. The MetaCat project delivers innovative tools
and knowledge for the identification of such robust 'all-round frequent hit' enzymes (AFHs). Metagenomic resources are being exploited by novel function- and sequence-based screenings to identify nitrilases, transaminases, ketoreductases, glycosyl hydrolases and lipases/esterases. A combination
of metagenomics and metacatalysis is being used together with structure-based and high-throughput technologies, generic model substrates mimicking challenging chemical synthesis steps, next generation sequencing technologies as well as in silico data mining. New genetic tools using synthetic
biology approaches are being developed to construct a cell-free function-based screening platform for faster and improved screening. The identified enzymes form a marketable versatile biocatalyst collection together with a comprehensive database and can be used as starting points for modeling
and in vitro evolution experiments. They will be applied to improve chemical production processes regarding e.g. timelines, purity of the products, environmental sustainability and will lead to value-added products. Thus, MetaCat contributes to shorten timelines for development of biotechnological
processes and thus makes industrial biocatalysis more attractive and profitable.
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