Antimicrobial development has focused on essential proteins (mainly enzymes) required for the pathogen to survive in culture (that is, in vitro). Although this approach has been successful in the past, antimicrobial resistance threatens our capacity to develop new drugs. Our results suggest that strategic protein–protein interactions in the host–pathogen interactome should be explored as putative drug targets that may lay the foundation of a new class of antimicrobials.

Our group focuses on understanding how protein-protein interactions participate in the infection progess. We aim to design new antibiotics based on the inhibition of host-pathogen complexes.

To fulfil their function, proteins need to interact with each other forming complexes. Understanding how pathogen proteins bind their host counterparts is important to explain how bacteria can infect, survive and proliferate inside cells. To achieve that, pathogen proteins mimic eukaryote interfaces to interact with the host. Our results suggest that host-pathogen protein-protein interactions are potential targets for a new generation of antimicrobials. If an interaction is required for the pathogen to infect the host, blocking this interaction would help to stop or delay the infection. In summary, treatments interfering with the adhesion and invasion of bacteria to host cells could be used as preventive strategies during surgical procedures or after infection by reducing the resistance of pathogens to known antibiotics by combating their spread in the organism

We aim to design new compounds, such as peptides, peptidomimetics and small drugs designed to interfere with such host-pathogen interactions to develop new antimicrobials.

Antimicrobial peptides (AMPs) are molecules found in all biological kingdoms responsible for the fight against microbial infections in the first steps of the immunological response. New strategies developed by bacteria and other microorganisms to evade classical antibiotics have urged the pharmaceutical industry to develop new drugs in order to wipe out these resistant microorganisms. In particular, AMPs have been proposed as promising candidates against these pathogens and offer important advantages such as broad range of activity and low toxicity and are less prone to give rise to resistant strains. 

Our group focuses on the design and improvement of AMPs as new antibiotics for drug-resistant bacteria. We use machine learning strategies for peptide activity prediction and structure-guided rational design to generate new leads.