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Simplified models for simulating replica exchange simulations and recovering kinetics of protein folding
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Text
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Title
Simplified models for simulating replica exchange simulations and recovering kinetics of protein folding
Identifier
ETD_1445
Identifier
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http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051081
Language
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eng
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theses
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Physics and Astronomy
Subject
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(authority = ETD-LCSH)
Topic
Protein folding
Subject
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(authority = ETD-LCSH)
Topic
Proteins--Structure
Abstract
Protein folding is a fundamental problem in modern structural biology. The nature of the problem poses challenges to the understanding of the process via
computer simulations. One of the challenges in the computer simulation of proteins at the atomic level is the efficiency of sampling conformational space. Replica exchange (RE) methods are widely employed to alleviate the difficulty. To study how to best employ RE to protein folding and binding problems, we constructed a kinetic network model for RE studies of protein folding and used this simplified model to carry out "simulations of simulations" to analyze how the underlying temperature dependence of the conformational kinetics and the basic parameters of RE all interact to affect the number of folding transitions observed. When protein folding follows anti-Arrhenius kinetics, we observe a speed limit for the number of folding transitions observed at the low temperature of interest, which depends on the maximum of the harmonic mean of the folding and unfolding transition rates at high temperature. The efficiency of temperature RE was also studied on a more complicated and realistic continuous two-dimensional potential. Comparison of the efficiencies obtained using the continuous and discrete models makes it possible to identify non-Markovian effects which slow down equilibration of the RE ensemble on the more complex continuous potential. In particular, the efficiency of RE is limited by the timescale of conformational relaxation within free energy basins. The other challenges we are facing in all-atom simulations is to obtain meaningful
information on the slow kinetics and pathways of folding. We present a kinetic network model which recover the kinetics using RE-generated states as the nodes of a kinetic network. Choosing the appropriate neighbors and the microscopic rates between the neighbors, the correct kinetics of the system can be recovered by running a simulation on the network.
computer simulations. One of the challenges in the computer simulation of proteins at the atomic level is the efficiency of sampling conformational space. Replica exchange (RE) methods are widely employed to alleviate the difficulty. To study how to best employ RE to protein folding and binding problems, we constructed a kinetic network model for RE studies of protein folding and used this simplified model to carry out "simulations of simulations" to analyze how the underlying temperature dependence of the conformational kinetics and the basic parameters of RE all interact to affect the number of folding transitions observed. When protein folding follows anti-Arrhenius kinetics, we observe a speed limit for the number of folding transitions observed at the low temperature of interest, which depends on the maximum of the harmonic mean of the folding and unfolding transition rates at high temperature. The efficiency of temperature RE was also studied on a more complicated and realistic continuous two-dimensional potential. Comparison of the efficiencies obtained using the continuous and discrete models makes it possible to identify non-Markovian effects which slow down equilibration of the RE ensemble on the more complex continuous potential. In particular, the efficiency of RE is limited by the timescale of conformational relaxation within free energy basins. The other challenges we are facing in all-atom simulations is to obtain meaningful
information on the slow kinetics and pathways of folding. We present a kinetic network model which recover the kinetics using RE-generated states as the nodes of a kinetic network. Choosing the appropriate neighbors and the microscopic rates between the neighbors, the correct kinetics of the system can be recovered by running a simulation on the network.
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electronic resource
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xvii, 110 p. : ill.
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Ph.D.
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Includes bibliographical references (p. 100-108)
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by Weihua Zheng
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Zheng
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Weihua
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Weihua Zheng
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Levy
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Ronald
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Ronald M Levy
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Morozov
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Alexandre
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Alexandre Morozov
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Haule
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Kristjan
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Kristjan Haule
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Van Heuvelen
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Alan
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Alan Van Heuvelen
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Gallicchio
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Emilio
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Emilio Gallicchio
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Rutgers University
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Graduate School - New Brunswick
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2009
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2009-01
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xx
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Rutgers University Electronic Theses and Dissertations
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ETD
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Graduate School - New Brunswick Electronic Theses and Dissertations
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rucore19991600001
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doi:10.7282/T3222V0H
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ETD doctoral
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The author owns the copyright to this work.
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Non-exclusive ETD license
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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