Title: SCH04: Computational design of DNAzymes as novel therapeutic molecules
Funding: Full time Home/EU fees and a stipend of £15,009 p.a. (terms & conditions)
Application deadline: 7 May 2019
Start date: October 2019
Duration: 3 years (full time)
Location: Colchester Campus
Based in: School of Biological Sciences (in collaboration with the School of Computer Science and Electronic Engineering)
This studentship is now closed to applicants. View our latest opportunities.
Gene therapy, particularly after the recent development of CRISPR technologies, has become the paradigm of disease treatment. However, a number of issues prevent these technologies to be as widespread as originally planned (including offsite targets and other technical difficulties).
We propose to utilise DNAzymes, short pieces of DNA capable of cleaving RNA, as novel therapeutics to target disease-related transcripts. DNAzymes recognize nucleotide residues within the target RNA via complementary binding arms and the catalytic core promotes phosphodiester bond cleavage of the target and generation of two RNA fragments. DNAzymes can therefore be designed to target any disease-causing factor within the cell, blocking its production and inhibiting the pathway.
DNAzymes have advantages over similar RNA-based therapeutics since they are cheaper to produce and have reduced off-target effects due to their high specificity and lack of immunogenicity in vivo. Indeed, clinical trials for asthma and nasopharyngeal carcinoma (for example) have shown that DNAzymes have a good efficacy and that they are safe.
In our lab we have made significant progress in the development of a much-needed treatment option for prostate cancer, by targeting androgen receptor transcripts with custom-made DNAzymes. However, the development of DNAzymes has been hampered by the lack of tools to assist with their development, making their design largely arbitrary, expensive and time consuming.
In the last few years we have developed a methodology to design DNAzymes, and we are currently testing these in the lab. Although we have successfully designed a number of molecules that target oncogenes (patent application submitted), our progress is limited by the lack of a fully developed computational and statistical framework to design and test DNAzymes in silico.
This PhD proposal aims to resolve this lack of design tools and to do this we will utilise the expertises of a bioinformatician (Marco, Biological Sciences), a computer scientist (Citi, CSEE) and a molecular biologist (Brooke, Biological Sciences).
Dr Marco will mostly supervise the programming and algorithm development aspects whilst Dr Citi will supervise the modelling parts. The biological relevance of designed DNAzymes and their efficacy in the lab will be evaluated under Dr Brooke’s guidance.
You will gain skills in bioinformatics, statistics, machine-learning and drug design, alongside broader transferable research skills; producing a highly employable postdoctoral researcher, with a range of multidisciplinary skills.
The award consists of a full Home/EU fee waiver or equivalent fee discount for overseas students (further fee details), a doctoral stipend equivalent to the Research Councils UK National Minimum Doctoral Stipend (£15,009 in 2019-20), plus £2,500 training bursary via Proficio funding, which may be used to cover the cost of advanced skills training including conference attendance and travel.
This is a multisciplinary project supervised by academics from two different departments. The primary supervisor will be Antonio Marco, who will oversees the algorithm and program developments, with advice from the other supervisors. Greg Brooke will be mostly involved in the experimental testing of the designed molecules and Luca Citi in the implementation of algorithms to increase the efficiency of the designed molecules.
We are looking for an enthusiastic person with a good undergraduate and/or master’s degree in a related subject (e.g. Computer Science, Mathematics, Bioinformatics, etc.) and an interest in computational biology.
Candidates with a degree in a Life Sciences field will also considered, provided that they have demonstrable experience in computational data analysis.
The ideal candidate should have programming experience. You must possess well-developed oral and written communication skills, interpersonal skills and be able to manage your time effectively
You can apply for this postgraduate research opportunity online.
Please upload with your application a CV, a covering letter, a personal statement and transcripts of any undergraduate or masters programmes.
Instruction to applicants
When you apply online you will be prompted to fill out several boxes in the form:
If you have any informal queries about this opportunity please email the lead supervisor, Dr Antonio Marco (email@example.com).
You can find the terms and conditions of this studentship here (PDF).