2024-25 Project (Hilpert & Nohturfft)

Peptide Power Meets AI Precision: Targeting WHO’s Most Wanted Pathogens

SUPERVISORY TEAM

Supervisor

Dr rer nat. Kai Hilpert at SGUL
Email: khilpert@sgul.ac.uk

Co-Supervisor

Dr Axel Nohturfft at SGUL
Email: anothurf@sgul.ac.uk

PROJECT SUMMARY

Project Summary

The Global Challenge:  The World Health Organization (WHO) has sounded the alarm: antibiotic resistance is jeopardizing global health, food security, and our very way of life. With over 1.2 million deaths in 2019 alone, we’re on the brink of an era where even minor injuries could turn fatal, and routine surgeries become high-risk endeavours. The very pillars of modern medicine are under threat.   

💡 Our Game-Changing Solution:  Enter Antimicrobial Peptides (AMPs) – nature’s very own defence mechanism. These diverse, naturally occurring molecules are one of our best bets against the looming shadow of multi-drug resistant bacteria. Their unique modes of action mean that we can develop a plethora of new drugs, bypassing the existing resistance mechanisms of menacing bacteria.   

🚀 Seize the Opportunity:    AMPs: Nature’s Goldmine – We’re not just talking theory; we have the capability and expertise to synthesize thousands of these peptides and rigorously test them for both their antimicrobial potency and safety.    Genomic Treasure Trove – With over 33,000 sequenced organisms at our fingertips and more being added daily, the potential for discovering novel AMPs is immense. And with state-of-the-art AI tools, we can efficiently mine this genomic gold, predicting and harnessing the power of new AMPs.   

🔬 Our Cutting-Edge Approach:  Harnessing the power of AI, we’ll predict the most potent peptides. We’ll then synthesize these peptides in bulk and put them to the test against formidable bacterial foes. Our comprehensive screening process ensures that only the best candidates move forward, where we’ll delve deeper into their antimicrobial prowess and safety profile. And for the pièce de résistance, we’ll unravel the mysteries of their mode of action.   

🏆 Proven Track Record:  Our preliminary studies have already showcased the potential of integrating AI tools with AMP research. And with a specialized lab that boasts 25 years of unparalleled experience in antimicrobial peptides, success isn’t just a possibility.    Are You Ready?  Join us in this groundbreaking endeavour. Together, we’ll not only combat antibiotic resistance but also pioneer the future of medicine. Be a part of the solution. Be a part of the revolution. 🌟🔬🌐

Project Key Words

antimicrobial peptides, artificial intelligence, multi-drug resistance

MRC LID Themes

  • Global Health = Yes
  • Health Data Science = No
  • Infectious Disease = Yes
  • Translational and Implementation Research = Yes

Skills

MRC Core Skills

  • Quantitative skills = Yes
  • Interdisciplinary skills = Yes
  • Whole organism physiology = Yes

Skills we expect a student to develop/acquire whilst pursuing this project

Basic microbiological skills to grow and test bacteria.
Ability to synthesize and analyse peptides.
Screening peptides for antimicrobial and cytotoxic activity.
Ability to use AI-based tools to predict and rank antimicrobial peptides.
Mode of action studies.

Routes

Which route/s is this project available for?

  • 1+4 = Yes
  • +4 = Yes

Possible Master’s programme options identified by supervisory team for 1+4 applicants:

  • LSHTM – MSc Immunology of Infectious Diseases
  • SGUL – MRes Biomedical Science – Infection and Immunity

Full-time/Part-time Study

Is this project available for full-time study? Yes
Is this project available for part-time study? Yes

Eligibility/Requirements

Particular prior educational requirements for a student undertaking this project

  • SGUL’s standard institutional eligibility criteria for doctoral study.

Other useful information

  • Potential CASE conversion? = No

PROJECT IN MORE DETAIL

Scientific description of this research project

Context and significance 
The World Health Organization (WHO) states that antibiotic resistance is one of the biggest threats to global health and food security, and leads to longer hospital stays, higher medical costs and increased mortality. In 2019 antibiotic resistance led to 1.2 million deaths. We  heading towards a time when common infections and minor injuries could once again become deadly because of drug resistance. Without a solution, even simple surgeries could become risky, threatening the foundation of modern medicine.  Antimicrobial peptides (AMPs) are seen as a potential solution. They are diverse, naturally occurring, and effective even against multi-drug resistant (MDR) bacteria. AMPs have diverse modes of action and therefore many different AMPs can be developed into new urgently needed drugs circumventing the exciting resistant mechanism of the bacteria.   

What is the opportunity? 
1) Antimicrobial peptides (AMPs) are a goldmine. They’re diverse, naturally occurring, active against multi-drug resistant (MDR) bacteria and fungi and show versatile modes of action. Hence, many AMPs can be developed into urgently needed drugs. We have the rare ability and expertise to synthesize thousands of AMPs and screen them for their antimicrobial and toxic activity.  
2) There is a huge, nearby untapped resource for novel AMPs, genomes. The increasingly available source of sequenced genomes includes over 18,000 whole genomes and 15,000 partially sequenced organisms. With the plummeting costs of sequencing, this repository continues to grow daily. There are cutting-edge AI tools available for free that can sift through whole genome data and predict novel AMPs.   

Techniques to be used 
Different AI tools will be used to predict the most active peptides. Peptide synthesis on cellulose will be used to produce large amounts of peptides. Classical microbiological methods will be used to grow bacteria. Screening will be performed by an established method. Most active peptides will be further investigated in terms of antimicrobial but also cytotoxic activity. In addition, mode of action studies will be performed.    

Previous studies on antimicrobial peptides were very successful and preliminary studies using AI tools have been successfully performed, demonstrating a high chance of success in a lab environment specialized in antimicrobial peptides with 25 years experience on that topic.

Further reading

(Relevant preprints and/or open access articles)

  • 10.3389/fchem.2017.00025
  • 10.1021/cb800240j

Additional information from the supervisory team

  • The supervisory team has provided a recording for prospective applicants who are interested in their project. This recording should be watched before any discussions begin with the supervisory team.
    Hilpert-Nohturrft Recording

MRC LID LINKS