Joseph S. Brown, PhD

Antibiotics are a cornerstone of modern-day medical care that continue to be challenged by bacterial resistance and exacerbated by decreased antibiotic development. Untreatable or resistant bacterial infections can become lethal, harkening back to a time before the discovery of efficacious antibiotics (e.g., penicillin). If unabated, antibiotic-resistant bacteria are projected to kill more people than cancer, heart disease, or diabetes in 2050. Thus, the development of new antibiotics is urgent. One of the most significant clinical threats comes from Gram-negative bacteria, due to their high rates of multi-drug resistance and virulence. Gram-negative antibiotic development is challenging, primarily because of the highly impenetrable cell-wall barrier, which in a variety of ways has single-handedly thwarted and limited the development of research. For this reason, Gram-negative antibiotic development must directly address the challenge of the cell-wall barrier. In our work, we will identify new therapeutics that potently antagonize outer membrane proteins on Gram-negative bacteria that are essential for their metabolism. We will kill these bacteria without needing to overcome the challenge of crossing the cell wall. Some peptide-like molecules, called peptidomimetics, have been discovered to work through this mechanism, but have only a modest binding affinity to their outer membrane target. Because of this, we hypothesize more potent peptidomimetics can be discovered and developed if they have a higher affinity. To discover these new molecules, we will use a technique called affinity selection that isolates high-affinity peptidomimetics to the outer membrane target protein from large chemically synthesized libraries containing hundreds of millions of compounds. Individual synthesis and testing of these molecules will establish the relationship binding affinity and potency and reveal their potential as new antibiotic candidates. Other outcomes of this work will potentially establish design rules for the intracellular penetration of peptidomimetics across bacterial membranes through similar discovery methods of affinity selection coupled to machine learning.