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PhD project title |
Machine-learning based design of light-driven biocatalysts for sustainable production of high-value industrial products |
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Outline description, including interdisciplinary, intersectoral and international dimensions |
Visible light is a cheap and environmentally friendly resource that can be used to accelerate chemical reactions. Despite of the widespread applications in chemistry, photocatalysis in biology is rare. Harnessing photochemistry in biological systems offers a promising route for harnessing clean energy and developing a light-dependent process, so it shows huge potential for biologically based manufacture. However, it is challenging to harness photochemistry in biomanufacture due to the elusive catalysis mechanism of the photoenzymes and the high cost involved in traditional directed evolution of enzymes. Machine learning, one of the artificial intelligence, has emerged as an promising method in predicting protein structures and function relationship using computers. In this project, a rational protein engineering approach combining computational simulations of enzymatic mechanism, machine-learning based rational design and genetic technique of directed evolution will be developed and tested on engineering an algal enzyme that uses visual light for hydrocarbon production, with the aim to expand the substrate scope and increase the selectivity of the enzyme and to make the laboratory evolution process more efficient. The proposed research would be valuable for developing novel methods for environmentally benign, highly efficient and precise synthesis of chiral hydrocarbon compounds, so as to provide excellent photoenzyme biocatalyst toolbox for selective biosynthesis of high-value hydrocarbon compounds, which are important for pharmaceutical and fine chemical industries. The ECR fellow will work on this interdisciplinary and inter-sectoral project, in close collaboration with the molecular biologists from the school of Biological Sciences, Zhejiang University, China and the Department of Biocatalysis and Isotope Chemistry, Almac, Norther Ireland. Further, the developed novel biotechnology will be handily exploited by Almac because of the long-standing and successful collaboration between Dr Huang and Almac, and therefore would be beneficial for Almac to develop its ultimate goal of becoming a worlding leading new technology-driven company. |
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Key words/descriptors
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Biocatalyst, Photoenzyme, Biomanufacture, Machine learning, Biosynthesis. |
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Fit to CITI-GENS theme(s) |
This proposal fits into three CITI-GENS themes including Information Technology, Life Sciences and Creative Industries. |
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Supervisor Information
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First Supervisor: Dr Meilan Huang School: CCE Second Supervisor: Dr Chris Law School: School of Biological Sciences Third Supervisor: Prof Tom Moody Company: Almac group |
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Name of non-HEI partner(s) |
Almac group |
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Contribution of non-HEI partner(s) to the project:
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The fellow will have close collaborations with the molecular biologists the biocatalysis group in Almac. After he/she has studied the structure-function relationship of the enzyme and designed new enzyme variants that may improve the enzyme's catalytic activity/selectivity and substrate scope using computational approaches, he/she will spend have a 3-month industrial placement at Almac in the second and third year to perform PCR expression and enzyme activity assays. Almac group is an organization headquartered in Northern Ireland that provides pharmaceutical development and manufacturing services to global pharmaceutical and biotech companies, with over 4,500 employees from EU, US, and Asia. He/she will also report to the third supervisor at Almac at regular basis to explore its potential application in industry |