Meilan Huang

    Meilan Huang


    Phone: +44 (0)28 9097 4698

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    Research Interests

    I have established a computational chemistry and biology group in the areas of computer-aided drug/material design and rational engineering enzymes as biocatalysts, having been engaged in developing and applying structure-based approaches to identify lead compounds or new biocatalysts. I have been supervising interdisciplinary research in collaboration with molecular biologists, biochemists and medicinal chemists from international renowned institutions such as Zhejiang Univ, Shanghai Jiaotong Univ, Beijing Univ of Chemical Technology, University of Malaya and industry such as Almac. 

    My group has developed novel statistical methods to design peptide inhibitors targeting protein-protein interactions as potential anti-virus therapy. Another research area is rationally engineering enzymes guided by theoretical modeling, where I have been the academic leader of the academia-industry collaborative project funded by Invest NI “Development of a computational and molecular biology platform for QUB and Almac”. Recently, I have developed research interest in rational design of new solar cell materials. The research has been published on international peer-reviewed high-impact journals such as ACS Catalysis, J Phys Chem, Biochemistry, Bioorg Med Chem Lett, Proteins, PLOS One, etc.

    Research Statement

    Rational enzyme engineering

    My research interest lies in rational protein engineering of enzymes for enantioselective biocatalysts. I am the academic leader of the interdisciplinary Invest NI bioengineering project composed of QUB and Almac scientists. We have rationally engineered various industrial enzymes in a number of industrial client projects with great success, which is exemplified by the recent success in rational design of (S)-selective transaminase. Selective conversion of bulky ketones to pure chiral amines is of great importance for the industry. By screening a small dataset of variants guided by interplay among molecular modelling, assay and bioinformatics analysis throughout the design process, the best designed variant contains only seven mutations and showed an improvement in reaction rate by > 1716-fold towards the bulky ketone, producing the corresponding enantiomerically pure chiral (S)-amine with the ee value of > 99%. Atomic level description of new variants with improved catalytic activity would provide a fundamental insight for further engineering the enzymes for production of a variety of industrially useful chiral amines.

    We have also been investigating the phosphorylation mechanism of GHMP kinases, in collaboration with molecular biologists from the School of Biological sciences at QUB. Despite of the clinical, pharmaceutical and biotechnical importance of this kinase family there is presently no drug therapies for the diseases associated with the family. Our ability to work in this field is compromised by the controversy surrounding the catalysis mechanism. Theoretical computing describes the electron transfer in the catalytic reaction and is a useful tool to understand the reaction mechanism. Little computational work has been done for the kinase family so far. Our QM/MM calculation on the potential energy surface disclosed a direct phosphorylation mechanism.

    Development of peptide inhibitors regulating protein-protein interactions 

    Another project ongoing in my group is developing new algorithm to design and optimize peptides to interrupt protein-protein interactions in the fusion process of enveloped (E) proteins. We developed a new Monto-Carlo biased optimization algorithm and demonstrated the new algorithm has been proved to be valid in predicting the regions which have potential to be developed into peptide inhibitors for E proteins, using three different classes of E proteins as test cases. Several hit peptides based on the Dengue2 E protein structure were designed and made and purified and their activities are being tested by our collaborators at University of Malaya. We developed a distance-dependant statistical potential specific to E-proteins including the E protein structural feature into the potential library. We developed repeat protein-specific statistical functions and demonstrated it is efficient to evaluate the stability of designed repeat proteins. The specific statistical function opens a way in development of novel binders to many important therapeutic targets such as HIV-1 and HSP70. A web server was developed: 

    We also developed a predictive machine learning model based on the peptide sequences to identify the active peptides that targeting envelope proteins. In this method, the model using discriminatory statistical function scores as input features obviously outperformed those using traditional physicochemical descriptors or amino acid composition, indicating the propensity of amino acid to be active or non-active would determine the activity of peptide inhibitors. This method would be useful in the development of antiviral therapies to target the initial step of virus infection, such as HIV, IFV, etc. 

    Structure-based design of cancer therapies 

    We have also been engaged in structure–based discovery of Grp78 (also called HSPA5) inhibitors. Grp78, a member of the HSP70 family is shown to be over-expressed in many cancers including prostate. The knockdown of Grp78 by siRNA has been shown to promote cancer cell death in particular in the context of loss of the tumour suppressor PTEN, therefore it represents an emerging prostate cancer target. Study on HSP70 inhibitor development is scarce and no drug-like HSP70 inhibitors have been identified so far.  By in silico screening of the commercially available NCI diversity libraries and an industry drug library, we identified several promising small-molecule hits that mimic the substrate peptide binding. Their inhibitory activities were validated by preliminary cancer and tumor -cell line assay. Currently, we have expanded development of inhibitors for the chaperone protein to chimeric peptides that would compete with the substrate binding or regulate the HSP organization protein (HOP) by interacting with its TPR1 domain, as well as engineering dual-binding peptides as potential Grp78 inhibitors.


    Awards and Funding

    2014: “New Biotechnology: Development of Computational and Molecular Biology Platforms for Almac and QUB” Invest NI, £763,210. Academic leader of the interdisciplinary research.

    2013: EPSRC NSCCS project CHEM708 "Phosphorylation mechanism of GHMP kinases by combined QM/MM calculation". 70,000 CPU hours

    2010: University strategic PhD studentship in collaboration with Univ. of Malaya.

    2009: Almac studentship in collaboration with Almac group.

    2008: Modeling Equipment fund for from Centre for Cancer research and Cell Biology at QUB (£40,000)

    2007: University McClay PhD studentship.

    2006: NSERC Visiting Fellowship “Application of Virtual Screening for the Identification and Optimization of Leads in Signaling Pathways”. Host Institute, Biotechnology Research Institute, National Research Council Canada. CAD$ 43,000.

    2004: Welcome Trust International Visiting Fellowship in Biomedical program “Computer-Aided Drug Design” Host Institute, University of Oxford. £69,000


    I have achieved PGCHET. Since I took the post, I have been building up my teaching load, delivering lectures to various levels of students, and have received good student feedback on my teaching. I have been coordinating three modules. In addition, developed the new MSci Medicinal chemistry course. I have been taken the duty of the school Examination Officier.


    I have been actively involved in international student recruitment activities. As the program coordinator, I initiated the corporations with Beijing University of Chemical Technology and Zhejiang University, Ningbo Institute of Technology, and procured the 2+2 and 3+1+1 MOAs with these universities. In addition, I procured the MOA with Inner Mongolia University. My duties include liaising with partner universities, coordinating course-matching, visiting partner universities to promote the program and interview potential students and coaching their applications and life at QUB. Since these programs were set up, a good number of self-funded international students from these partner universities have enrolled in the various joint programs provided by our school every year.

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