Dokument: Netzwerkmodelle und strukturelle Merkmale der Oligomerbildung von Amyloid-β-Peptiden und Huntingtin-Proteinen auf der Grundlage von Molekulardynamiksimulationen im Mikrosekundenbereich

Titel:	Netzwerkmodelle und strukturelle Merkmale der Oligomerbildung von Amyloid-β-Peptiden und Huntingtin-Proteinen auf der Grundlage von Molekulardynamiksimulationen im Mikrosekundenbereich
Weiterer Titel:	Network Models and Structural Characteristics of Oligomer Formation of Amyloid-β Peptides and Huntingtin Proteins Based on Microsecond Timescale Molecular Dynamics Simulations
URL für Lesezeichen:	https://docserv.uni-duesseldorf.de/servlets/DocumentServlet?id=63082
URN (NBN):	urn:nbn:de:hbz:061-20230817-105054-2
Kollektion:	Dissertationen
Sprache:	Englisch
Dokumententyp:	Wissenschaftliche Abschlussarbeiten » Dissertation
Medientyp:	Text
Autor:	Khaled, Mohammed Abdalhalim Mohammed [Autor]
Dateien:	[Dateien anzeigen] Adobe PDF [Details] 57,80 MB in einer Datei [ZIP-Datei erzeugen] Dateien vom 03.07.2023 / geändert 03.07.2023
Beitragende:	Prof.Dr. Strodel,Birgit [Gutachter] Prof. Dr. Schröder, Gunnar [Gutachter]
Stichwörter:	Compuational Biochemistry / Computational Biophysics
Dewey Dezimal-Klassifikation:	500 Naturwissenschaften und Mathematik » 540 Chemie
Beschreibung:	Intrinsically disordered proteins (IDPs) are abundant in the human proteome and often associated with amyloid-related diseases, such as Alzheimer's and Huntington's disease. While IDPs can aggregate into insoluble fibrillar β-sheet aggregates, they can also form soluble, intermediate-size aggregates called oligomers that are highly toxic and are polymorphic. Studying oligomers in detail has been a significant challenge, and the availability of experimental methods for their thermodynamic and kinetic characterization is limited due to the low abundance and the transit nature of the oligomer. Molecular dynamics (MD) simulation provides a powerful tool to investigate their behavior on the atomistic scale. Additionally, advanced methods for analyzing MD simulations, such as Markov state models and transition networks, have enable a detailed exploration of the conformational landscapes of the oligomers. To this end, we utilized all-atom MD simulations to investigate the aggregation of amyloid-β (Aβ) peptides and Huntingtin (Htt) proteins into small oligomers. Specifically, our studies include the following: (i) In our first study, we conducted multiple MD simulations totaling 0.3 ms of Aβ42 oligomers, including dimers, tetramers, and hexamers, which were then analyzed using Markov state models and transition networks. Our analysis revealed that the oligomers can occupy multiple states, and transitions between these states occur within microseconds. These findings demonstrate the feasibility of characterizing the kinetics and thermodynamics of Aβ42 oligomers using network analysis. (ii) We conducted research on the structures and mechanisms of aggregation for different Aβ variants into oligomers. Our findings indicated that Aβ variants lacking the ability to fold into a β-hairpin structure, as present in the Aβ40 peptide, are unable to form oligomers. (iii) We also compered the formation of Aβ42 dimers in solution and at the neuronal membrane. In solution, the dimerization process involves a transition from a random coil to a β-sheet structure, which is a key step towards amyloid aggregation. However, our findings show that when Aβ42 dimers interact with the neuronal membrane, they are less likely to adopt a β-sheet structure. (iv) Finally, we investigated the conformational and dynamical effects of polyglutamine expansion and its flanking domains on the folding and dimerization of Htt proteins. Our findings revealed significant distinctions between the nonpathogenic and pathogenic Htt monomers, which directly affect their dimerization. In summary, by utilizing MD simulations and advanced analysis methods, our approach provides a detailed understanding of the aggregation of Aβ oligomers and Htt proteins at the atomic level. The investigations conducted in this thesis are valuable in comprehending the initial stages of the amyloid aggregation process, which can facilitate the development of prospective treatments for Amyloid-related diseases.
Lizenz:	Dieses Werk ist lizenziert unter einer Creative Commons Namensnennung 4.0 International Lizenz
Fachbereich / Einrichtung:	Mathematisch- Naturwissenschaftliche Fakultät » WE Chemie » Theoretische Chemie und Computerchemie
Dokument erstellt am:	17.08.2023
Dateien geändert am:	17.08.2023
Promotionsantrag am:	11.04.2023
Datum der Promotion:	08.05.2023