RT info:eu-repo/semantics/bachelorThesis
T1 Revisión de las metodologías computacionales y bioinformáticas para asistir al desarrollo de nuevos fármacos
A1 Fajardo Benítez, Juana María
A2 Grado En Farmacia
K1 Bioinformática
K1 Fármacos
K1 Métodos computacionales
K1 Estructura química
K1 Programa informático
K1 AI
K1 Deep Learning
AB This Final Degree Project shows a detailed review of the different computational andbioinformatic methodologies to assist drug development. Where it is narrated from theoldest to the most advanced. The work has been divided into three scales: a molecularscale, an atomic scale and a mixture of the two previous scales, that is, thismethodology works for both the atomic and molecular scales.At the atomic scale we will focus on the Molecular Dynamic simulator, since it iswidely used today, especially in neuroscience. In this section we will comment on theQSARs, which are very important in the different stages of drug development and theirrole in these.Regarding the molecular scale, we will focus on the methodology that is most usedtoday, such as docking. We will also see other methodologies with their importance,such as SELEX, and the advances that it has left. They also highlight a reducedsimulation that is the Grain Course, it is even gaining repercussions in recent years.Finally, we will deal with the innovative Artificial Intelligence, and how two resurgentmethods, such as Machine Learning and Deep Learning, are entering the pharmaceuticalmarket, innovating and developing as one more methodology.Likewise, we want to highlight with this review that any of these methodologies can beused for preventive medicine, that is why we give examples of different diseases orpathologies and thus find out if these techniques are useful in this area, which is increasingly leading our attention. modern medicine.
YR 2022
FD 2022
LK http://riull.ull.es/xmlui/handle/915/29962
UL http://riull.ull.es/xmlui/handle/915/29962
LA es
DS Repositorio institucional de la Universidad de La Laguna
RD 08-nov-2024