Background
Antimicrobial resistance (AMR) is rising rapidly around the world, causing over 1 million deaths worldwide in 2019. This number is expected to rise to over 10 million deaths by 2050 if our dwindling antibiotic arsenal is not replenished. Recently we have shown that transition metal complexes have promising antimicrobial properties while not being more toxic towards human cells than purely organic molecules.1,2 In the Frei Lab we are interested in exploring, developing and understanding metal complexes as antimicrobial agents. We are employing efficient synthetic methodologies together with automation and machine learning to systematically explore the metalloantibiotic chemical space.
Promising hit-compounds are rationally explored further with structure-activity studies and in-depth biological evaluations for activity spectrum, toxicity, stability etc. We are also interested in understanding the mechanism of action of promising compounds through a variety of biochemical and microbiology techniques.
This PhD project will entail sub-projects in all three pillars of our research. The student will explore modular and automated synthesis of new libraries of metal complexes (such as explored by our group recently3). These will be evaluated for their biological properties. This data will be used to both identify promising compounds but also to train machine-learning models to guide subsequent synthesis rounds towards even better molecules. The most promising compounds will be systematically modified to explore structure-activity relationships. Lastly the student will focus on a selection of promising compounds to explore in-depth their biological effects on bacteria.
The ultimate goal will be to identify lead compounds that will go into in vivo studies while also advancing our scientific understanding on how metalloantibiotics achieve their biological effects.
Objectives
- Setting up the high-throughput automated synthesis of new metal complexes (both manually and by utilising automated synthesis systems (ChemSpeed, Opentrons)
- Evaluating the antibacterial profile of the synthesized compounds to identify the ones with the best activity profile
- Rational chemical development of promising compounds utilising medicinal chemistry approaches
- Investigation of the mechanism of action of lead compounds utilising microbiology techniques (including microscopy, plate reader assays, mass spectrometry and more)
- Optional: Utilisation of the obtained data to train machine learning models able to predict subsequent generations of antibacterial metal compounds.
Experimental Approach
This is a highly interdisciplinary approach involving synthetic organic and inorganic chemistry, microbiology and computational approaches. The candidate student will be trained in a wide range of laboratory techniques and approaches and also develop new methodologies and assays throughout the project. With the large amount of data that will be generated, skills in data handling, analysis and visualisation will also be trained.
Novelty
The field of metalloantibiotics is still very young, meaning that most of this work will be cutting edge. Additionally, automation and machine learning have not yet been applied to this field making this project one of the first to explore this area of research. The mode of action of only a handful of metalloantibiotics has been studied so far. Any insights in this area will be of high importance and impact in the field. Lastly because of the urgent need for new antibiotics, there is a real potential for the commercialisation if a promising class of metalloantibiotics is discovered.
Training
The project will provide training in synthetic organic and inorganic chemistry, purification and characterisation techniques. On the biological side the PhD student will be trained on microbiological and cell biology assays. Depending on the interest and aspirations of the student, further training on the development of automation protocols and machine learning can be included. Short scientific exchanges with research groups experienced in in-depth mode of action studies and/or in vivo studies are possible.
You will follow our core cohort-based training programme to support the development of scientific, transferable and employability skills, as well as training on specific techniques and equipment. Training includes employability and professionalism, graduate teaching assistant training and guidance on writing papers. https://www.york.ac.uk/chemistry/postgraduate/training/idtc/idtctraining/
There will be opportunities for networking and sharing your work both within and beyond the University. Funding is provided to enable you to attend conferences and external training. The department also runs a varied and comprehensive seminar programme.
Equality and Diversity
The Department of Chemistry holds an Athena SWAN Gold Award and is committed to supporting equality and diversity for all staff and students. The Department strives to provide a working environment which allows all staff and students to contribute fully, to flourish, and to excel: https://www.york.ac.uk/chemistry/ed/ . As part of our commitment to Equality and Diversity, and Widening Participation, we are working with the YCEDE project (https://ycede.ac.uk/) to improve the number of under-represented groups participating in doctoral study.
Entry requirements
You should hold or expect to achieve the equivalent of at least a UK upper second class degree in Chemistry or a relevant related subject. Check the entry requirements for your country: https://www.york.ac.uk/study/international/your-country/
English language requirements: https://www.york.ac.uk/study/postgraduate-research/apply/international/english/
For more information about the project, click on the supervisor's name above to email them.
For more information about the application process or funding, please click on email institution
Guidance for applicants: https://www.york.ac.uk/chemistry/postgraduate/apply/
Submit an online PhD in Chemistry application: https://www.york.ac.uk/study/postgraduate/courses/apply?course=DRPCHESCHE3
The closing date for applications is 3 January but may close earlier if a suitable candidate is identified.
The start date of the PhD will be 16 September 2024
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