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Genetic Algorithm-Driven Protein Engineering: Enhancing PT8 Poly morphic Toxins for Biotechnology

dc.contributor.advisorVanneshi, Leonardo
dc.contributor.advisorGal, Maayan
dc.contributor.authorLisboa Maia Correia Rodrigues, Luísa
dc.date.accessioned2025-04-09T15:55:00Z
dc.date.available2025-04-09T15:55:00Z
dc.date.issued2024-07-22
dc.description.abstract"Polymorphic toxins, such as PT8 from the Leptospiraceae family, play a significant role in mi crobial competition and have potential applications in biotechnology. However, their toxicity often limits their utility in practical applications. This thesis presents a novel approach to opti mizing the PT8 polymorphic toxin for biotechnological use through the use of genetic algo rithms (GAs) and machine learning models to reduce its inherent toxicity while maintaining functional integrity. In this study, we first analyzed the structure and dynamics of PT8 using state-of-the-art protein structure prediction tools like AlphaFold, RosettaFold, and ESMFold, coupled with molecular dynamics simulations. These analyses revealed several key regions within PT8 that contribute to its stability and function but also underlie its toxicity(...)"pt_PT
dc.description.versionN/Apt_PT
dc.identifier.tid203774698
dc.identifier.urihttp://hdl.handle.net/10362/181980
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherUniversidade NOVA de Lisboa. Instituto de Tecnologia Química e Biológica António Xavier.pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectPT8pt_PT
dc.subjectbiotechnologypt_PT
dc.subjectgenetic algorithmspt_PT
dc.subjectPolymorphic toxinspt_PT
dc.subjectmicrobial competition,pt_PT
dc.titleGenetic Algorithm-Driven Protein Engineering: Enhancing PT8 Poly morphic Toxins for Biotechnologypt_PT
dc.typemaster thesis
dspace.entity.typePublication
oaire.citation.conferencePlaceOeiras, Portugalpt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT

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