Nanomarker for early detection of Alzheimer’s disease combining ab initio DFT simulations and molecular docking approach
The tau protein is considered an important qualitative and quantitative biomarker for Alzheimer’s disease in its asymptomatic phase. In 2011, biomarkers were suggested by the National Institute on Aging-Azheimer’s Association as a new criterion for the early diagnosis of Alzheimer’s disease. Thus, h...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universidad de Santiago de Compostela (USC) |
| Repositorio: | Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela |
| Idioma: | inglés |
| OAI Identifier: | oai:minerva.usc.gal:10347/44149 |
| Acceso en línea: | https://hdl.handle.net/10347/44149 |
| Access Level: | acceso abierto |
| Palabra clave: | Ab initio-DFT Bionanomarker Molecular docking Nanotechnology Tau protein |
| Sumario: | The tau protein is considered an important qualitative and quantitative biomarker for Alzheimer’s disease in its asymptomatic phase. In 2011, biomarkers were suggested by the National Institute on Aging-Azheimer’s Association as a new criterion for the early diagnosis of Alzheimer’s disease. Thus, highlighting the non-existence of theoretical research on the subject, we investigated the binding interaction properties between phosphorylated tau protein and a theoretically modeled ligands constituted by the fullerol functionalized with radiopharmaceuticals from an in silico approach via molecular docking and density functional theory (DFT) ab initio computational simulation. The results demonstrated that the ligand with the greatest affinity-based binding energy to the protein was fullerol + F-THK5105. However, all systems were considered promising for the development of a potential diagnostic nanomarker. These theoretical results could efficiently contribute to reduce the time and the cost for future experimental preclinical studies and open new opportunities toward molecular recognition in nanomedicine |
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