COMPUTATIONAL MODELING OF BACTERIAL OUTER MEMBRANES AND DEVELOPMENT OF HIGH-THROUGHPUT SCREENING PLATFORM FOR ANTIBIOTICS
Date of Award
Doctor of Philosophy (PhD)
Biomedical and Chemical Engineering
Antibiotic resistance, computational platform, Gram-negative bacteria, outer membrane, porins
Antibiotic resistance is a major health challenge because it limits the treatment options for common infectious diseases and will cause 10 million deaths each year after 2050. There is an urgent need to reduce the misuse of antibiotics and seek new classes of antibiotics that induce less or no resistance. Despite the push for new therapeutics, there has been a precipitous decline in the number of newly approved antibacterial drugs due to a limited understanding of how bacteria adapt to the chemical stress stimuli. The development of antimicrobial resistance is especially true for Gram-negative bacteria that develop resistance to antibiotics readily due to their unique highly charged outer membrane. Structurally, the Gram-negative bacteria is highly asymmetric bilayer that comprises of an inner leaflet of phospholipids and an outer leaflet of lipopolysaccharides. Embedded in the bilayer are outer membrane proteins (OMPs) that form pores to allow passage of nutrients and other small molecules through the cell wall. In addition to the outer membrane, the Gram-negative bacteria have a thin peptidoglycan layer and an inner phospholipid membrane that surrounds the cytosol. All potential small molecule antibiotic molecule have to navigate through all three layers of the Gram-negative bacterial cell wall before targeting the cellular functions. There is, however, limited understanding of the chemical specificity, structure, and functional aspects of each layer in the cell wall. To enhance our understanding of the bacterial cell wall, we first developed molecular models of ten commensal or human pathogenic bacterial species: Pseudomonas aeruginosa, Escherichia coli, Helicobacter pylori, Porphyromonas gingivalis, Bacteroides fragilis, Bordetella pertussis, Chlamydia trachomatis, Campylobacter jejuni, Neisseria meningitidis, and Salmonella minnesota. Second, we studied the self-assembly of OMPs that in some cases form trimers in the outer membranes to perform their function. In the third step, we combined the outer membrane models and the OMPs to build a computational screening platform to quantify the transport properties of molecules across a bacterial outer membrane. The goal of the computational platform is to provide high-throughput screening of vast libraries of small molecules that have the potential of being active antibacterial agents against Gram-negative bacteria. A computational platform has merit to producing reliable first-round screening of molecules at a fraction of the cost in the otherwise expensive drug-discovery pipeline.
Ma, Huilin, "COMPUTATIONAL MODELING OF BACTERIAL OUTER MEMBRANES AND DEVELOPMENT OF HIGH-THROUGHPUT SCREENING PLATFORM FOR ANTIBIOTICS" (2019). Dissertations - ALL. 1005.