It is predicted that by 2050 there will be 10 million deaths annually due to super-resistant bacterial infections. Antimicrobial resistance (AMR) is already responsible for nearly 5 million deaths a year. Ribosomes serve as an ideal drug target being frequently targeted by antibiotics and having a highly conserved structure with few options for resistance. However, computer aided drug design (CADD) using ribosome crystal structures presents several challenges and is underutilized in the field. In this work we establish a successful protocol for antibiotic redocking and docking within the high interest sites of the peptidyl transferase center (PTC). Molecular visualization and interaction mapping were used to atomistically delineate binding patterns in the ribosomal PTC that could be used for CADD. Eleven ribosome crystal structures were validated for computational testing, which revealed derivative binding patterns in the A-site and P-site that can be used to increase antibiotic efficacy. Ribosome overlays revealed high interaction frequency nucleotides that were widely conserved throughout the different species and could be used to inform bidentate design to target two pockets at once. This work serves as a basis for methods to computationally explore drug optimization on ribosome targeting antibiotics to help combat the rapid expansion of AMR. / Master of Science in Life Sciences / Antimicrobial resistance (AMR) to antibiotics by bacteria is a rapidly increasing problem. Current trends predict that there will be more death due to super-resistant bacterial strains than cancer by 2050. Ribosomes are essential cellular machinery for bacteria and make an ideal antibiotic target. Using computational tools to optimize antibiotics with available ribosome crystal structural data presents several challenges and is underutilized throughout the field. In this work we establish a successful protocol for determining and exploiting antibiotic binding patterns within the functional center of the ribosome, the peptidyl transfer center (PTC). Nearly a dozen ribosome crystal structures were validated for computational testing, and binding patterns were revealed within the PTC that allowed antibiotic derivatives with increased efficacy to be developed. Ribosome validation also helped inform new drug class design so that multiple drug sites could be targeted at once, which were docked sharing high frequency nucleotide interactions with both parent antibiotics. This work serves as a basis for methods to computationally explore drug optimization on ribosome targeting antibiotics to help combat the rapid expansion of AMR.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/119176 |
| Date | 29 May 2024 |
| Creators | Briganti, Anthony Joseph |
| Contributors | Biochemistry, Brown, Anne M., Lowell, Andrew Nesemann, Lemkul, Justin Alan |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | Creative Commons Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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