BIOTECH & LIFE SCIENCES biocatalystsdesigner
A collaboration between a team of enzyme engineers and a leading computational biologist promises to transform the industrial biocatalysis landscape, Nicola Brittain reports
R
esearchers at the Manchester Institute of Biotechnology (MIB) and the Institute for Protein Design at the
University of Washington, recently received funding of £1.2m to set up an initiative called The International Centre For Enzyme Design which looks set to transform the design and engineering of enzymes for industrial applications. The project, launched in November
and to run for an initial four years, is a partnership between a group of University of Manchester UK academics and an international overseas partner, Professor David Baker, a renowned computational biologist based at the University of Washington. The consortium will use deep learning and computational techniques to create sustainable, industrial biocatalysts in a timely and cost-eff ective way. Eurolab caught up with Anthony
Green, director of the MIB, and Sarah Lovelock, a senior lecturer in the MIB, two of the lead researchers with the partnership to fi nd out what the project will mean for business, the environment, and enzyme scientists more widely.
THE PROJECT EXPLAINED Green explained that the programme brings together leading computational and experimental teams to create a step-change in the speed of biocatalyst development. The methods developed will also allow
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The new computational design process will save time and money
the development of new families of enzymes with valuable activities that are unknown in nature. The Manchester-based team of
scientists currently make use of experimental enzyme engineering techniques such as ‘directed evolution’ to create new biocatalysts for use in the chemical industry. This process aims to expedite the natural evolution of biological molecules and systems through iterative rounds of gene diversifi cation and library screening. Green said: “The process is extremely powerful, but it’s also expensive, time consuming and requires specialist infrastructure.” The new collaboration, and the
resulting incorporation of advanced deep-learning methods for protein design pioneered by the Baker lab, will accelerate the enzyme development pipeline and potentially provide access to enzyme functions that are currently unavailable. The enzymes developed will be
used for the sustainable manufacture of pharmaceuticals, including new therapeutic modalities, alongside other applications such as bioremediation (to help break down environmental pollutants), recycling of plastics, synthesis of fl avours and fragrances, and production of bio-based fuels and commodity chemicals from renewable feedstocks.
WHY NOW? The idea of designing new enzymes computationally has been around for decades, but the deep learning tools that have been developed recently off er a suff iciently high degree of accuracy, predictability of output and speed to make the researchers optimistic that the reliable design of eff icient enzymes is within reach. These outcomes are likely to have wide-ranging impacts across the chemical industry, especially in the pharmaceutical sector for which time to market is extremely important.
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