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.
DataGenome
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