Artificial cyclic peptide library for novel antimicrobial resistance therapeutics and targeted delivery

Antimicrobial Resistance (AMR) is one of the biggest global health threats of our time where deaths per year expected to be 10 million by 2050. The bacterial cell envelope constitutes a stringent multi-layered barrier that is virtually impermeable to all biologics, including nucleic acids. Despite being a crucial barrier, the permeability of the bacterial envelopes is still poorly understood.

Understanding how to design drugs able to circumvent the bacterial envelope barrier could, undoubtedly, boost the pool of antibacterial drugs dramatically.

A library of natural and unnatural amino acids peptide library will be applied and the ideal strong binder artificial molecule would be predicted with the help of Artificial Intelligence (AI) and be applied for targeted delivery of therapeutic oligonucleotides and siRNA. The library could also lead to a discovery of very potent antibiotic, especially for the antimicrobial resistance strains.

The project, with multidisciplinary nature, will add experimental skills and knowledge in organic chemistry and acquire knowledge and skills in oligonucleotides synthesis, biophysical/biochemical cell biology/machine learning assays. The library is a general method which will not only help to design ligands as antibiotic but also can be applied in future, as a delivery agent for nucleic acids such as ASO and siRNA.

The library could also be applied for diagnostic if a reporter dye be attached to the ligand. All the results can lead to also better understanding of the delivery hurdles.