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Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/222271
Development and application of computational methodologies for novel therapeutic strategies based on protein-protein interactions
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[eng] Protein-protein interactions (PPIs) are essential for the proper functioning of biological systems, regulating key cellular processes such as protein degradation, signaling, and immune responses. This makes them both promising drug targets and a foundation for novel therapeutic strategies. In this thesis, we employ computational approaches to study PPIs, leveraging advances in protein structure prediction alongside our group’s expertise in biomolecular simulations. Given that AlphaFold2 was launched at the beginning of this work, we first assess the robustness of its predictions by simulating prospective scenarios in drug discovery. Building on these insights, we then investigate PPIs in various biological contexts, including: (i) the characterization of a PPI involved in plant’s fungal infections, which could serve as a starting point for the development of new antifungal treatments; (ii) the study of the ternary complex formed between an E3 ligase and a target protein in the presence of PROTAC molecules, providing structural and stability insights for the rational optimization of PROTACs; (iii) the identification of PPIs between de novo protein binders based on the ubiquitin scaffold with high success rate; and (iv) the generation of protein immunogens to elicit an immune response against the West Nile Virus. Overall, we demonstrate that combining molecular simulations with Artificial Intelligence tools—including AlphaFold2, MaSIF and newly developed protein design techniques—offers a powerful approach to study the intrinsic dynamics of PPIs and generates structural insights that can guide the rational design of novel therapeutic strategies.
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DÍAZ ROVIRA, Anna maria. Development and application of computational methodologies for novel therapeutic strategies based on protein-protein interactions. [consulta: 5 de desembre de 2025]. [Disponible a: https://hdl.handle.net/2445/222271]