Modeling Protein Conformational Dynamics Using Kinetic Network Models

Modeling Protein Conformational Dynamics Using Kinetic Network Models PDF Author: Zhaoning Cui
Publisher:
ISBN:
Category : Proteins
Languages : en
Pages : 151

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Modeling Protein Conformational Dynamics Using Kinetic Network Models

Modeling Protein Conformational Dynamics Using Kinetic Network Models PDF Author: Zhaoning Cui
Publisher:
ISBN:
Category : Proteins
Languages : en
Pages : 151

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Book Description


Protein Conformational Dynamics

Protein Conformational Dynamics PDF Author: Ke-li Han
Publisher: Springer Science & Business Media
ISBN: 3319029703
Category : Medical
Languages : en
Pages : 488

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Book Description
This book discusses how biological molecules exert their function and regulate biological processes, with a clear focus on how conformational dynamics of proteins are critical in this respect. In the last decade, the advancements in computational biology, nuclear magnetic resonance including paramagnetic relaxation enhancement, and fluorescence-based ensemble/single-molecule techniques have shown that biological molecules (proteins, DNAs and RNAs) fluctuate under equilibrium conditions. The conformational and energetic spaces that these fluctuations explore likely contain active conformations that are critical for their function. More interestingly, these fluctuations can respond actively to external cues, which introduces layers of tight regulation on the biological processes that they dictate. A growing number of studies have suggested that conformational dynamics of proteins govern their role in regulating biological functions, examples of this regulation can be found in signal transduction, molecular recognition, apoptosis, protein / ion / other molecules translocation and gene expression. On the experimental side, the technical advances have offered deep insights into the conformational motions of a number of proteins. These studies greatly enrich our knowledge of the interplay between structure and function. On the theoretical side, novel approaches and detailed computational simulations have provided powerful tools in the study of enzyme catalysis, protein / drug design, protein / ion / other molecule translocation and protein folding/aggregation, to name but a few. This work contains detailed information, not only on the conformational motions of biological systems, but also on the potential governing forces of conformational dynamics (transient interactions, chemical and physical origins, thermodynamic properties). New developments in computational simulations will greatly enhance our understanding of how these molecules function in various biological events.

Metastability and Markov State Models in Molecular Dynamics

Metastability and Markov State Models in Molecular Dynamics PDF Author: Christof Schütte
Publisher: American Mathematical Soc.
ISBN: 0821843591
Category : Mathematics
Languages : en
Pages : 141

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Book Description
Applications in modern biotechnology and molecular medicine often require simulation of biomolecular systems in atomic representation with immense length and timescales that are far beyond the capacity of computer power currently available. As a consequence, there is an increasing need for reduced models that describe the relevant dynamical properties while at the same time being less complex. In this book the authors exploit the existence of metastable sets for constructing such a reduced molecular dynamics model, the so-called Markov state model (MSM), with good approximation properties on the long timescales. With its many examples and illustrations, this book is addressed to graduate students, mathematicians, and practical computational scientists wanting an overview of the mathematical background for the ever-increasing research activity on how to construct MSMs for very different molecular systems ranging from peptides to proteins, from RNA to DNA, and via molecular sensors to molecular aggregation. This book bridges the gap between mathematical research on molecular dynamics and its practical use for realistic molecular systems by providing readers with tools for performing in-depth analysis of simulation and data-analysis methods. Titles in this series are co-published with the Courant Institute of Mathematical Sciences at New York University.

Simplified Models for Simulating Replica Exchange Simulations and Recovering Kinetics of Protein Folding

Simplified Models for Simulating Replica Exchange Simulations and Recovering Kinetics of Protein Folding PDF Author: Weihua Zheng
Publisher:
ISBN:
Category : Protein folding
Languages : en
Pages : 110

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Book Description
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.

Coarse-grained Modeling of Protein Dynamics Using Elastic Network Models

Coarse-grained Modeling of Protein Dynamics Using Elastic Network Models PDF Author: Silke Andrea Wieninger
Publisher:
ISBN:
Category :
Languages : en
Pages : 206

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An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation

An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation PDF Author: Gregory R. Bowman
Publisher: Springer Science & Business Media
ISBN: 9400776063
Category : Science
Languages : en
Pages : 148

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Book Description
The aim of this book volume is to explain the importance of Markov state models to molecular simulation, how they work, and how they can be applied to a range of problems. The Markov state model (MSM) approach aims to address two key challenges of molecular simulation: 1) How to reach long timescales using short simulations of detailed molecular models. 2) How to systematically gain insight from the resulting sea of data. MSMs do this by providing a compact representation of the vast conformational space available to biomolecules by decomposing it into states sets of rapidly interconverting conformations and the rates of transitioning between states. This kinetic definition allows one to easily vary the temporal and spatial resolution of an MSM from high-resolution models capable of quantitative agreement with (or prediction of) experiment to low-resolution models that facilitate understanding. Additionally, MSMs facilitate the calculation of quantities that are difficult to obtain from more direct MD analyses, such as the ensemble of transition pathways. This book introduces the mathematical foundations of Markov models, how they can be used to analyze simulations and drive efficient simulations, and some of the insights these models have yielded in a variety of applications of molecular simulation.

Efficient Sampling of Protein Conformational Dynamics and Prediction of Mutation Effects

Efficient Sampling of Protein Conformational Dynamics and Prediction of Mutation Effects PDF Author: Hongbin Wan
Publisher:
ISBN:
Category :
Languages : en
Pages : 166

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Book Description
Molecular dynamics (MD) simulation is a powerful tool enabling researchers to gain insight into biological processes at the atomic level. There have been many advancements in both hardware and software in the last decade to both accelerate MD simulations and increase their predictive accuracy; however, MD simulations are typically limited to the microsecond timescale, whereas biological motions can take seconds or longer. Because of this, it remains extremely challenging to restrain simulations using ensemble-averaged experimental observables. Among various approaches to elucidate the kinetics of molecular simulations, Markov State Models (MSMs) have proven their ability to extract both kinetic and thermodynamic properties of long-timescale motions using ensembles of shorter MD simulation trajectories. In this dissertation, we have implemented an MSM path-entropy method, based on the idea of maximum-caliber, to efficiently predict the changes in protein folding behavior upon mutation. Next, we explore the accuracy of different MSM estimators applied to trajectory data obtained by adaptive seeding, in which new rounds of short MD simulations are collected from states of interest, and propose a simple method to build accurate models by population re-weighting of the transition count matrix. Finally, we explore ways to reconcile simulated ensembles with Hydrogen/Deuterium exchange (HDX) protection measurements, by constructing multi-ensemble Markov State Models (MEMMs) from biased MD simulations, and reconciling these predictions against the experimental data using the BICePs (Bayesian Inference of Conformational Populations) algorithm. We apply this approach to model the native-state conformational ensemble of apomyoglobin at neutral pH.

Normal Mode Analysis

Normal Mode Analysis PDF Author: Qiang Cui
Publisher: CRC Press
ISBN: 142003507X
Category : Mathematics
Languages : en
Pages : 448

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Book Description
Rapid developments in experimental techniques continue to push back the limits in the resolution, size, and complexity of the chemical and biological systems that can be investigated. This challenges the theoretical community to develop innovative methods for better interpreting experimental results. Normal Mode Analysis (NMA) is one such technique

Investigating Conformational Transitions of Proteins by Coarse-grained Elastic Network Models

Investigating Conformational Transitions of Proteins by Coarse-grained Elastic Network Models PDF Author: Mustafa Tekpinar
Publisher:
ISBN:
Category :
Languages : en
Pages : 96

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Book Description
Proteins are large molecular machines. Many of these machines carry out conformationaltransitions to perform function. It is very difficult to determine all metastable proteinconformations experimentally. Therefore, computational methods have been developed toinvestigate metastable protein conformations and conformational transitions. For most ofproteins, atomistic molecular dynamics cannot reach the time scales of conformationaltransitions, which are typically beyond microseconds. The large size of proteins is anotherobstacle in atomistic molecular dynamics simulations. Coarse-grained elastic network modelscan provide an alternative to overcome the time scale and size problems. In this dissertation, we have investigated conformational transitions of proteins by using modified elasticnetwork models. These models can be applied in two ways. First, they allow us to analyzeconformational transition pathways and deduce the dynamic order of structural events. Second, they enable us to build models for unknown protein conformations by incorporatingexperimental data. For the first application, a transition pathway modeling method callediENM will be presented in Chapter 2. For the second application, a flexible fitting methodbased on small angle X-ray scattering (SAXS) data will be discussed in Chapter 3. Ourmethods will be compared to alternative methods and they will be validated by experimentaldata.

Protein Actions

Protein Actions PDF Author: Ken Dill
Publisher: Garland Science
ISBN: 1351815008
Category : Medical
Languages : en
Pages :

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Book Description
Protein Actions: Principles and Modeling is aimed at graduates, advanced undergraduates, and any professional who seeks an introduction to the biological, chemical, and physical properties of proteins. Broadly accessible to biophysicists and biochemists, it will be particularly useful to student and professional structural biologists and molecular biophysicists, bioinformaticians and computational biologists, biological chemists (particularly drug designers) and molecular bioengineers. The book begins by introducing the basic principles of protein structure and function. Some readers will be familiar with aspects of this, but the authors build up a more quantitative approach than their competitors. Emphasizing concepts and theory rather than experimental techniques, the book shows how proteins can be analyzed using the disciplines of elementary statistical mechanics, energetics, and kinetics. These chapters illuminate how proteins attain biologically active states and the properties of those states. The book ends with a synopsis the roles of computational biology and bioinformatics in protein science.