| Seznam |
| Téma: | Analysis of Molecular Dynamic Simulations for Alzheimer's Disease Research using Neural Networks |
|---|---|
| Katedra: | Katedra kybernetiky |
| Vedoucí: | Josef Šivic |
| Vypsáno jako: | Diplomová práce, Bakalářská práce, Semestrální projekt |
| Popis: | One of the characteristics of Alzheimer's disease (AD) is the formation of neurotoxic aggregates of Aβ42 peptide. Understanding the dynamic properties of this protein is a key to determine the effects of drug candidates for potential AD treatment. The objective of this project is to analyze the kinetic properties of the Aβ42 peptide via Markov state models and possibly propose better drug candidates for potential AD treatment. The project will build on existing results computed on molecular dynamics simulations using VAMPnets neural networks. For a detailed description please see:
https://docs.google.com/document/d/1FO3kUAXlwcUQ2A1tldTQ4LO_Hu1KhOYqgQf7N6t9DO8/edit#bookmark=kix.p08dmwchuxqj |
| Literatura: | T Löhr, K Kohlhoff, G T Heller, C Camilloni, M Vendruscolo. A kinetic ensemble of the Alzheimer’s Aβ peptide. Nature Computational Science, 2021.
A Mardt, L Pasquali, H Wu, F Noe. VAMPnets for deep learning of molecular kinetics. Nat Commun 9, 2018. |