scholarly journals Predicting the Kinetics of RNA Oligonucleotides Using Markov State Models

2017 ◽  
Vol 13 (2) ◽  
pp. 926-934 ◽  
Author(s):  
Giovanni Pinamonti ◽  
Jianbo Zhao ◽  
David E. Condon ◽  
Fabian Paul ◽  
Frank Noè ◽  
...  
Keyword(s):  
Markov State ◽  
Markov State Models ◽  
State Models ◽  
Kinetics Of

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 Improved Kinetics of Molecular Simulations using Biased Markov State Models

2016 ◽  
Vol 110 (3) ◽  
pp. 523a
Author(s):  
Joseph F. Rudzinski ◽  
Kurt Kremer ◽  
Tristan Bereau
Keyword(s):  
Molecular Simulations ◽  
Markov State ◽  
Markov State Models ◽  
State Models ◽  
Kinetics Of

scholarly journals Markov State Models Reveal a Two-Step Mechanism of miRNA Loading into the Human Argonaute Protein: Selective Binding followed by Structural Re-arrangement

2015 ◽  
Vol 11 (7) ◽  
pp. e1004404 ◽  
Author(s):  
Hanlun Jiang ◽  
Fu Kit Sheong ◽  
Lizhe Zhu ◽  
Xin Gao ◽  
Julie Bernauer ◽  
...  
Keyword(s):  
Argonaute Protein ◽  
Selective Binding ◽  
Markov State ◽  
Markov State Models ◽  
State Models ◽  
Step Mechanism
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