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PhD projects

-Rational Enzyme Engineering of Biocatalysts for Synthetic Biology -Computational Photocatalysis -Computer-Aided Molecular Design and Optimization -Development of Structure-Based Statistical Potentials -Machine learning-Informed Catalyst Design

20022022

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Personal profile

Particulars

Dr Meilan Huang joined Queen’s University Belfast in 2007 as a lecturer. She worked with Prof Fengling Qing's in the Key Laboratory of Organoflorine Chemistry at Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences in 1998-1999. After awarded a PhD degree in Computational Chemistry at Zhejiang University in Feb 2003, she was a postdoc working with Prof Arvi Rauk in the Department of Chemistry at University of Calgary Canada. She was a Welcome Trust research fellow in the Laboratory of Physical and Theoretical Chemistry at University of Oxford working with Prof W. Graham Richards, FRS in 2004-2006 and a research fellow working with Prof Artem Cherkasov in Department of Medicine, University of British Columbia, Canada in 2006-2007. She is a Fellow of Royal Society of Chemistry (FRSC) and a Fellow of Royal Society of Biology (FRSB).

Her main research area is developing and applying Computational methods for biocatalysis. She studies the interactions and catalytic mechanism  of various enzymes to direct the rational design of novel biocatalysts for chemical transformations. She published over 60 full research articles in high-impact peer-reviewed journals. She is the corresponding author of many publications in top chemistry journals including ACS Catalysis, (2022, 12: 4037),  Chem Comm (2020, 56: 9356 & 2019, 55: 2198), J Am Chem Soc (2019, 141: 19, 7934), Nature Communications (2019, 10: 3198), ACS Catalysis (2016, 6: 11, 7749).

She has led the Computational team in several interdisciplinary reserach projects. She was the PI of Chemistry in the interdisciplinary biotechnological project “Development of a computational and molecular biology platform between QUB and Almac” (2015-2019). She is the PI of chemistry in a new 3-year project (2021-2024) INSIGHT@ "IN Silico-Informed metaGenomic Harvesting Technology", in close collaboration with experimentalists and industry. So far, she has secured over £2m research income with a share of £688k. As the principle supervisor, she has supervised 2 computational postdocs and currently is supervising another computational postdoc.

Research Interests

Computational Chemistry and Biology;

Enzyme Engineering;

Biocatalysis;

Rational Drug Design;

Photocatalytis;

Statistical algorithm and Machine Learning

Teaching

PGCHET

CHM1015: Skills for Physical Chemistry (Module Coordinator) (2011-2021)

CHE1006/CHE1104: Maths for Chemists and Engineers (2021-present)

CCE1102: Physical Theory

CHM3005C: Computational Chemistry in Drug Discovery (2019-present) (Module Coordinator)

CHM4007: Frontier in Medicinal Chemistry (2013-2019) (Module coordinator)

CHM3010: Practical Skills in Chemistry (Module Coordinator)

CHM3016: Drug Development

CHM4001: Chemistry Research Project

CHM7004: Research Project

CCE Summer School programme (Programme Lead) 

Achievements

2017: Queen's Student Union "Education Excellence Award" 

2021: Newton Fund Research Links Workshop grant-2020-RLWK12-10149 "Catalytic Chemistry and Chemical Technology of C1 process" British Council. PI

2021-2023: Royal Society: IEC\NSFC\201177 - International Exchanges 2020 “Machine Learning-assisted Directed Evolution of Enzymes”. PI

2021-2024: "INSIGHT: IN Silico Informed metaGenomic Harvesting Technology platform - Development of an advanced and secure enzyme discovery platform for Almac and QUB" Invest NI, RD11181114, £1,299,329. PI of Chemistry

2015-2019: "New Biotechnology: Development of Computational and Molecular Biology Platforms for Almac and QUB" Invest NI, RD3014092, £981,360.  PI of Chemistry

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 7 - Affordable and Clean Energy

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