Browsing by Subject "Antimicrobial peptides"
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Item Exploring protein biochemistry with deep learning(2023-12) Kulikova, Anastasiya Vitalievna; Wilke, C. (Claus); Davies, Bryan W.; Klivans, Adam R.; Russell, RickDeep learning has become widely used in biological sciences. More specifically, the development of protein deep learning models has leveraged the evergrowing collection of biological data to learn the patterns that govern protein biochemistry. Here, we focus on the assessment of different protein deep learning models to better understand each of their capabilities, benefits and drawbacks. Our work aims to provide insights for future protein engineering efforts and for the discovery of protein homologs. In Chapter 2 we assessed a structure-based protein ML model in its ability to make biochemically meaningful predictions and tested weather or not the model can predict specific allowed amino acids in a protein. We compared the performance of models trained on different input sizes and correlated model predictions with natural variation in order to better understand how these models learn protein structure and biochemistry. In Chapter 3, we compared the predictions of two structure models and two language models to determine if different protein representations affect what information each model type learns and their performance. Finally, in Chapter 4, we apply a sequence-based protein model to searching for antibacterial microcin peptides in bacterial genomes.Item Understanding antimicrobial resistance mechanisms and the production of antimicrobial peptides in E. coli(2023-12) Hohne, Brielle; Kumar, Manish, Ph. D.; Keitz, Benjamin K.; Werth, Charles; Rosales, Adrianne; Contreras, LydiaAntimicrobial resistance is a growing threat to global health. One pathway to confer antimicrobial resistance is through the overexpression of multidrug (MDR) efflux pumps, making them important to study. Antimicrobial peptides (AMPs) are ideal candidates to explore for synergistic effects with antibiotics to revive the efficacy of antibiotics which are subject to resistance. This dissertation work aims to understand the mechanism the MDR efflux pump, AcrAB, that confers antimicrobial resistance to E. coli, and create a method to express the AMPs, Moringa oleifera chitin-binding protein (MOCBP) and Moringa oleifera coagulant protein (MOCP), in E. coli for future study. In this dissertation, we determined the transport rates of protons and substrates through the proton driven pump, AcrAB. We used two optical spectroscopic techniques, stopped flow and fluorescence correlation spectroscopy, in concert to estimate average transport through AcrAB incorporated into lipid vesicles. This research not only addresses the urgent public health concern of antimicrobial resistance but also pioneers a photonically enabled in vitro assay, opening new possibilities for the study and development of proton-coupled transporters and their inhibitors. We also developed a novel expression system in E. coli for MOCP and MOCBP and optimized the purification methods. MOCP and MOCBP are antimicrobial peptides found in Moringa oliefera seed protein extract. Both platforms were shown to be scalable, allowing for future studies of and alterations to their properties and functions. This has the potential for future applications in food safety, water purification, and cosmetic products.