SURF1 i AlphaFold2: desxifrant la síndrome de Leigh: la utilitat de la biologia estructural i la bioinformàtica demostrada a través de l'estudi estructural i filogenètic in silico de la proteïna SURF1
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- dc.contributor.author Plans Gandia, Laia
- dc.date.accessioned 2024-04-24T11:35:58Z
- dc.date.available 2024-04-24T11:35:58Z
- dc.date.issued 2024
- dc.description Primer Premi del XIX Premi PRBB al millor treball de recerca en Medicina i Ciències de la Vidaca
- dc.description Tutor: Oriol Gandia (daina.isard, cooperativa d'ensenyament -Olesa de Montserrat-)
- dc.description.abstract During the last years, the field of bioinformatics has evolved at a frenetic pace, producing new programmes able to store data or predict protein structures or sequences. This research aims to prove the potential of this new technology carrying on a bioinformatics research which analyzes the protein whose mutations cause the Leigh syndrome, SURF1, using the prediction computational approach AlphaFold2 to obtain structural information about the molecular basis of the disease to finally set that a specific mutation disturbs the interaction between SURF1 and COX1. Using a structural approach to study the impact of mutations in SURF1 provides useful information to perform in vitro and in vivo studies and proves the vast potential that this technology has.ca
- dc.format.mimetype application/pdf
- dc.identifier.uri http://hdl.handle.net/10230/59893
- dc.language.iso catca
- dc.rights © Tots els drets reservatsca
- dc.rights.accessRights info:eu-repo/semantics/openAccessca
- dc.subject.other Síndrome de Leigh
- dc.title SURF1 i AlphaFold2: desxifrant la síndrome de Leigh: la utilitat de la biologia estructural i la bioinformàtica demostrada a través de l'estudi estructural i filogenètic in silico de la proteïna SURF1ca
- dc.type info:eu-repo/semantics/otherca