Computational antibody och peptide design to fight antimicrobial resistance

Bacterial infections, such as sepsis, kill millions each year, and the problem is aggravated by the rapid rise of anti-microbial resistance (AMR).

Animal studies have shown that interfering with the ability to bind host proteins can make a pathogen that usually kills its host in 3 days harmless.

I here propose to use computationally designed antibodies and peptides to interfere with host-pathogen protein-protein interactions (PPIs) to lower the pathogens virulence grade and, thereby, systematically explore the possibility to develop a new class of species-specific antimicrobial compounds.

I propose a project with four work packages (WPs):WP1: Develop a new TX-MS-based protocol to structurally model antibody-antigen interactions.WP2: Use RosettaDesign to design antibody sequences with higher affinity, express them, and evaluate them by developing a new computational tool, qTX-MS.WP3: Develop a peptide-design method that uses the antibody-antigen models as input, capturing the features responsible for the high affinity and test the designed peptides using qTX-MS.WP4: The optimized antibodies and peptide designs will be tested in an approach consisting of adsorption of host proteins onto living bacteria followed by quantitative measurements, a test to see if a disrupted interaction alters the interaction between the bacteria and immune cells using a quantitative phagocytosis assay, we recently developed.