Markov State Models for Protein and RNA Folding
Markov State Models for Protein and RNA Folding

Author: Gregory Ross Bowman

Publisher: Stanford University

Published: 2010

Total Pages: 279

ISBN-13:

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Understanding the molecular bases of human health could greatly augment our ability to prevent and treat diseases. For example, a deeper understanding of protein folding would serve as a reference point for understanding, preventing, and reversing protein misfolding in diseases like Alzheimer's. Unfortunately, the small size and tremendous flexibility of proteins and other biomolecules make it difficult to simultaneously monitor their thermodynamics and kinetics with sufficient chemical detail. Atomistic Molecular Dynamics (MD) simulations can provide a solution to this problem in some cases; however, they are often too short to capture biologically relevant timescales with sufficient statistical accuracy. We have developed a number of methods to address these limitations. In particular, our work on Markov State Models (MSMs) now makes it possible to map out the conformational space of biomolecules by combining many short simulations into a single statistical model. Here we describe our use of MSMs to better understand protein and RNA folding. We chose to focus on these folding problems because of their relevance to misfolding diseases and the fact that any method capable of describing such drastic conformational changes should also be applicable to less dramatic but equally important structural rearrangements like allostery. One of the key insights from our folding simulations is that protein native states are kinetic hubs. That is, the unfolded ensemble is not one rapidly mixing set of conformations. Instead, there are many non-native states that can each interconvert more rapidly with the native state than with one another. In addition to these general observations, we also demonstrate how MSMs can be used to make predictions about the structural and kinetic properties of specific systems. Finally, we explain how MSMs and other enhanced sampling algorithms can be used to drive efficient sampling.

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

Author: Gregory R. Bowman

Publisher: Springer Science & Business Media

Published: 2013-12-02

Total Pages: 148

ISBN-13: 9400776063

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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.

Metastability and Markov State Models in Molecular Dynamics
Metastability and Markov State Models in Molecular Dynamics

Author: Christof Schütte

Publisher: American Mathematical Soc.

Published: 2013-12-26

Total Pages: 141

ISBN-13: 0821843591

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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.

Biological Sequence Analysis
Biological Sequence Analysis

Author: Richard Durbin

Publisher: Cambridge University Press

Published: 1998-04-23

Total Pages: 372

ISBN-13: 113945739X

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Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

Protein Conformational Dynamics
Protein Conformational Dynamics

Author: Ke-li Han

Publisher: Springer Science & Business Media

Published: 2014-01-20

Total Pages: 488

ISBN-13: 3319029703

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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.

Computational Approaches for Understanding Dynamical Systems: Protein Folding and Assembly
Computational Approaches for Understanding Dynamical Systems: Protein Folding and Assembly

Author:

Publisher: Academic Press

Published: 2020-03-05

Total Pages: 554

ISBN-13: 0128211377

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Computational Approaches for Understanding Dynamical Systems: Protein Folding and Assembly, Volume 170 in the Progress in Molecular Biology and Translational Science series, provides the most topical, informative and exciting monographs available on a wide variety of research topics. The series includes in-depth knowledge on the molecular biological aspects of organismal physiology, with this release including chapters on Pairwise-Additive and Polarizable Atomistic Force Fields for Molecular Dynamics Simulations of Proteins, Scale-consistent approach to the derivation of coarse-grained force fields for simulating structure, dynamics, and thermodynamics of biopolymers, Enhanced sampling and free energy methods, and much more. - Includes comprehensive coverage on molecular biology - Presents ample use of tables, diagrams, schemata and color figures to enhance the reader's ability to rapidly grasp the information provided - Contains contributions from renowned experts in the field

Stochastic Processes in Physics and Chemistry
Stochastic Processes in Physics and Chemistry

Author: N.G. Van Kampen

Publisher: Elsevier

Published: 1992-11-20

Total Pages: 482

ISBN-13: 0080571387

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This new edition of Van Kampen's standard work has been completely revised and updated. Three major changes have also been made. The Langevin equation receives more attention in a separate chapter in which non-Gaussian and colored noise are introduced. Another additional chapter contains old and new material on first-passage times and related subjects which lay the foundation for the chapter on unstable systems. Finally a completely new chapter has been written on the quantum mechanical foundations of noise. The references have also been expanded and updated.

Computational Approaches for Studying Enzyme Mechanism Part B
Computational Approaches for Studying Enzyme Mechanism Part B

Author:

Publisher: Academic Press

Published: 2016-08-03

Total Pages: 538

ISBN-13: 0128111089

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Computational Approaches for Studying Enzyme Mechanism, Part B is the first of two volumes in the Methods in Enzymology series that focuses on computational approaches for studying enzyme mechanism. The serial achieves the critically acclaimed gold standard of laboratory practices and remains one of the most highly respected publications in the molecular biosciences. Each volume is eagerly awaited, frequently consulted, and praised by researchers and reviewers alike. Now with over 550 volumes, the series remains a prominent and essential publication for researchers in all fields of the life sciences and biotechnology, including biochemistry, chemical biology, microbiology, synthetic biology, cancer research, genetics, and other fields of study. - Focuses on computational approaches for studying enzyme mechanism - Continues the legacy of this premier serial with quality chapters authored by leaders in the field - Covers research methods in intermediate filament associated proteins, and contains sections on such topics as lamin-associated proteins, intermediate filament-associated proteins and plakin, and other cytoskeletal cross-linkers

Pacific Symposium on Biocomputing 2010, Kamuela, Hawaii, USA, 4-8 January 2010
Pacific Symposium on Biocomputing 2010, Kamuela, Hawaii, USA, 4-8 January 2010

Author: Russ B. Altman

Publisher: World Scientific

Published: 2009-10-23

Total Pages: 502

ISBN-13: 9814295299

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The Pacific Symposium on Biocomputing (PSB) 2010 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2010 will be held on January 4 - 8, 2010 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference. PSB 2010 will bring together top researchers from the US, Asia Pacific, and around the world to exchange research results and address pertinent issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology. The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's "hot topics". In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.