scholarly journals Fibril Growth Behavior of Amyloid β on Polymer-Based Planar Membranes: Implications for the Entanglement and Hydration of Polymers

2021 ◽  
Vol 11 (10) ◽  
pp. 4408
Author(s):  
Toshinori Shimanouchi ◽  
Miki Iwamura ◽  
Shintaro Deguchi ◽  
Yukitaka Kimura
Keyword(s):  
Quartz Crystal ◽  
Phosphatidyl Ethanolamine ◽  
Amyloid Β ◽  
Growth Behavior ◽  
Artificial Organs ◽  
Amyloid Β Peptide ◽  
Polymer Backbone ◽  
Dipalmitoyl Phosphatidylcholine ◽  
Planar Membranes ◽  
Kinetics Of

The design of biosensors and artificial organs using biocompatible materials with a low affinity for amyloid β peptide (Aβ) would contribute to the inhibition of fibril growth causing Alzheimer’s disease. We systematically studied the amyloidogenicity of Aβ on various planar membranes. The planar membranes were prepared using biocompatible polymers, viz., poly(methyl methacrylate) (PMMA), polysulfone (PSf), poly(L-lactic acid) (PLLA), and polyvinylpyrrolidone (PVP). Phospholipids from biomembranes, viz., 1,2-dioleoyl-phosphatidylcholine (DOPC), 1,2-dipalmitoyl-phosphatidylcholine (DPPC), and polyethylene glycol-graft-phosphatidyl ethanolamine (PEG-PE) were used as controls. Phospholipid- and polymer-based membranes were prepared to determine the kinetics of Aβ fibril formation. Rates of Aβ nucleation on the PSf- and DPPC-based membranes were significantly higher than those on the other membranes. Aβ accumulation, calculated by the change in frequency of a quartz crystal microbalance (QCM), followed the order: PSf > PLLA > DOPC > PMMA, PVP, DPPC, and PEG-PE. Nucleation rates exhibited a positive correlation with the corresponding accumulation (except for the DPPC-based membrane) and a negative correlation with the molecular weight of the polymers. Strong hydration along the polymer backbone and polymer–Aβ entanglement might contribute to the accumulation of Aβ and subsequent fibrillation.

scholarly journals Thermodynamics and kinetics of the amyloid-β peptide revealed by Markov state models based on MD data in agreement with experiment

2021 ◽  
Author(s):  
Arghadwip Paul ◽  
Suman Samantray ◽  
Marco Anteghini ◽  
Mohammed Khaled ◽  
Birgit Strodel
Keyword(s):  
Amyloid Β ◽  
Md Simulations ◽  
Amyloid Β Peptide ◽  
Intrinsically Disordered ◽  
Thermodynamics And Kinetics ◽  
Markov State ◽  
Markov State Models ◽  
State Models ◽  
Kinetics Of

The convergence of MD simulations is tested using varying measures for the intrinsically disordered amyloid-β peptide (Aβ). Markov state models show that 20–30 μs of MD is needed to reliably reproduce the thermodynamics and kinetics of Aβ.

scholarly journals Thermodynamics and kinetics of the amyloid-β peptide revealed by Markov state models based on MD data in agreement with experiment

2020 ◽  
Author(s):  
Arghadwip Paul ◽  
Suman Samantray ◽  
Marco Anteghini ◽  
Birgit Strodel
Keyword(s):  
Alzheimer’S Disease ◽  
Force Fields ◽  
Amyloid Β ◽  
Md Simulations ◽  
Amyloid Β Peptide ◽  
Thermodynamics And Kinetics ◽  
Markov State ◽  
Markov State Models ◽  
State Models ◽  
Kinetics Of

AbstractThe amlyoid-β peptide (Aβ) is closely linked to the development of Alzheimer’s disease. Molecular dynamics (MD) simulations have become an indispensable tool for studying the behavior of this peptide at the (sub)molecular level, thereby providing insight into the molecular basis of Alzheimer’s disease. General key aspects of MD simulations are the force field used for modeling the peptide or protein and its environment, which is important for accurate modeling of the system of interest, and the length of the simulations, which determines whether or not equilibrium is reached. In this study we address these points by analyzing 30-µs MD simulations acquired for Aβ40 using seven different force fields. We assess the convergence of these simulations based on the convergence of various structural properties and of NMR and fluorescence spectroscopic observables. Moreover, we calculate Markov state models for each of the seven MD simulations, which provide an unprecedented view of the thermodynamics and kinetics of the amyloid-β peptide. This further allows us to provide answers for pertinent questions, like: Which force fields are suitable for modeling Aβ? (a99SB-UCB and a99SB-ILDN/TIP4P-D); What does Aβ peptide really look like? (mostly extended and disordered) and; How long does it take MD simulations of Aβ to attain equilibrium? (20–30 µs). We believe the analyses presented in this study will provide a useful reference guide for important questions relating to the structure and dynamics of Aβin particular, and by extension other similar disordered peptides.

scholarly journals Modeling the Inhibition Kinetics of Curcumin, Orange G, and Resveratrol with Amyloid-β Peptide

ACS Omega ◽  
2021 ◽  
Author(s):  
Chandra Mouli R. Madhuranthakam ◽  
Arash Shakeri ◽  
Praveen P. N. Rao
Keyword(s):  
Amyloid Β ◽  
Amyloid Β Peptide ◽  
Inhibition Kinetics ◽  
Orange G ◽  
Kinetics Of

scholarly journals Surface Plasmon Resonance Binding Kinetics of Alzheimer’s Disease Amyloid β Peptide-Capturing and Plaque-Binding Monoclonal Antibodies

Biochemistry ◽  
2009 ◽  
Vol 48 (43) ◽  
pp. 10405-10415 ◽  
Author(s):  
Muthu Ramakrishnan ◽  
Karunya K. Kandimalla ◽  
Thomas M. Wengenack ◽  
Kyle G. Howell ◽  
Joseph F. Poduslo
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Monoclonal Antibodies ◽  
Surface Plasmon Resonance ◽  
Surface Plasmon ◽  
Plasmon Resonance ◽  
Amyloid Β ◽  
Binding Kinetics ◽  
Amyloid Β Peptide ◽  
Kinetics Of

Amyloid β-peptide and Alzheimer's disease

2014 ◽  
Vol 56 ◽  
pp. 99-110 ◽  
Author(s):  
David Allsop ◽  
Jennifer Mayes
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Senile Plaques ◽  
Strong Support ◽  
Amyloid Β ◽  
Amyloid Β Peptide ◽  
Amyloid Cascade Hypothesis ◽  
Sequence Of Events ◽  
Aβ Amyloid ◽  
Amyloid Cascade

One of the hallmarks of AD (Alzheimer's disease) is the formation of senile plaques in the brain, which contain fibrils composed of Aβ (amyloid β-peptide). According to the ‘amyloid cascade’ hypothesis, the aggregation of Aβ initiates a sequence of events leading to the formation of neurofibrillary tangles, neurodegeneration, and on to the main symptom of dementia. However, emphasis has now shifted away from fibrillar forms of Aβ and towards smaller and more soluble ‘oligomers’ as the main culprit in AD. The present chapter commences with a brief introduction to the disease and its current treatment, and then focuses on the formation of Aβ from the APP (amyloid precursor protein), the genetics of early-onset AD, which has provided strong support for the amyloid cascade hypothesis, and then on the development of new drugs aimed at reducing the load of cerebral Aβ, which is still the main hope for providing a more effective treatment for AD in the future.

Insights into amyloid disease from fly models

2014 ◽  
Vol 56 ◽  
pp. 69-83 ◽  
Author(s):  
Ko-Fan Chen ◽  
Damian C. Crowther
Keyword(s):  
Drosophila Melanogaster ◽  
Neurodegenerative Disorders ◽  
Amyloid Β ◽  
Amyloid Β Peptide ◽  
Disease Pathogenesis ◽  
Amyloid Aggregates ◽  
Aβ Amyloid ◽  
Polypeptide Chains ◽  
Amyloid Diseases

The formation of amyloid aggregates is a feature of most, if not all, polypeptide chains. In vivo modelling of this process has been undertaken in the fruitfly Drosophila melanogaster with remarkable success. Models of both neurological and systemic amyloid diseases have been generated and have informed our understanding of disease pathogenesis in two main ways. First, the toxic amyloid species have been at least partially characterized, for example in the case of the Aβ (amyloid β-peptide) associated with Alzheimer's disease. Secondly, the genetic underpinning of model disease-linked phenotypes has been characterized for a number of neurodegenerative disorders. The current challenge is to integrate our understanding of disease-linked processes in the fly with our growing knowledge of human disease, for the benefit of patients.

Analytical methods to explore Amyloid-β-Peptide variants beyond Aβ1-40 and Aβ1-42

2015 ◽  
Vol 48 (06) ◽  
Author(s):  
H Esselmann ◽  
C Hafermann ◽  
O Jahn ◽  
I Kraus ◽  
J Vogelgsang ◽  
...  
Keyword(s):  
Analytical Methods ◽  
Amyloid Β ◽  
Amyloid Β Peptide
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