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The chemical and biological sciences face unprecedented opportunities in the 21st century. A confluence of factors from parallel universes - advances in experimental techniques in biomolecular structure determination, progress in theoretical modeling and simulation for large biological systems, and breakthroughs in computer technology - has opened new avenues of opportunity as never before. Now, experimental data can be interpreted and further analysed by modeling, and predictions from any approach can be tested and advanced through companion methodologies and technologies. This two volume set describes innovations in biomolecular modeling and simulation, in both the algorithmic and application fronts. With contributions from experts in the field, the books describe progress and innovation in areas including: simulation algorithms for dynamics and enhanced configurational sampling, force field development, implicit solvation models, coarse-grained models, quantum-mechanical simulations, protein folding, DNA polymerase mechanisms, nucleic acid complexes and simulations, RNA structure analysis and design and other important topics in structural biology modeling. The books are aimed at graduate students and experts in structural biology and chemistry and the emphasis is on reporting innovative new approaches rather than providing comprehensive reviews on each subject.
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.
Molecular Modeling of Proteins, Second Edition provides a theoretical background of various methods available and enables non-specialists to apply methods to their problems by including updated chapters and new material not covered in the first edition. This detailed volume opens by featuring classical and advanced simulation methods as well as methods to set-up complex systems such as lipid membranes and membrane proteins and continues with chapters devoted to the simulation and analysis of conformational changes of proteins, computational methods for protein structure prediction, usage of experimental data in combination with computational techniques, as well as protein-ligand interactions, which are relevant in the drug design process. Written for the highly successful Methods in Molecular Biology series, chapters include thorough introductions, step-by-step instructions and notes on troubleshooting and avoiding common pitfalls. Update-to-date and authoritative, Molecular Modeling of Proteins, Second Edition aims to aid researchers in the physical, chemical and biosciences interested in utilizing this powerful technology.
"The chapters in this book survey the progress in simulating biomolecular dynamics.... The images conjured up by this work are not yet universally loved, but are beginning to bring new insights into the study of biological structure and function. The future will decide whether this scientific movement can bring forth its Picasso or Modigliani." –from the Foreword by Peter G. Wolynes, Bullard-Welch Foundation Professor of Science, Rice University This book highlights the state-of-art in coarse-grained modeling of biomolecules, covering both fundamentals as well as various cutting edge applications. Coarse-graining of biomolecules is an area of rapid advances, with numerous new force fields having appeared recently and significant progress made in developing a systematic theory of coarse-graining. The contents start with first fundamental principles based on physics, then survey specific state-of-art coarse-grained force fields of proteins and nucleic acids, and provide examples of exciting biological problems that are at large scale, and hence, only amenable to coarse-grained modeling. Introduces coarse-grained models of proteins and nucleic acids. Showcases applications such as genome packaging in nuclei and understanding ribosome dynamics Gives the physical foundations of coarse-graining Demonstrates use of models for large-scale assemblies in modern studies Garegin A. Papoian is the first Monroe Martin Associate Professor with appointments in the Department of Chemistry and Biochemistry and the Institute for Physical Science and Technology at the University of Maryland.
Very broad overview of the field intended for an interdisciplinary audience; Lively discussion of current challenges written in a colloquial style; Author is a rising star in this discipline; Suitably accessible for beginners and suitably rigorous for experts; Features extensive four-color illustrations; Appendices featuring homework assignments and reading lists complement the material in the main text
Computational modeling is emerging as a powerful new approach to study and manipulate biological systems. Multiple methods have been developed to model, visualize, and rationally alter systems at various length scales, starting from molecular modeling and design at atomic resolution to cellular pathways modeling and analysis. Higher time and length scale processes, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. This book provides an overview of the established computational methods used for modeling biologically and medically relevant systems.
In Protein Structure, Stability, and Folding, Kenneth P. Murphy and a panel of internationally recognized investigators describe some of the newest experimental and theoretical methods for investigating these critical events and processes. Among the techniques discussed are the many methods for calculating many of protein stability and dynamics from knowledge of the structure, and for performing molecular dynamics simulations of protein unfolding. New experimental approaches presented include the use of co-solvents, novel applications of hydrogen exchange techniques, temperature-jump methods for looking at folding events, and new strategies for mutagenesis experiments. Unique in its powerful combination of theory and practice, Protein Structure, Stability, and Folding offers protein and biophysical chemists the means to gain a more comprehensive understanding of some of this complex area by detailing many of the major techniques in use today.
Protein folding is a process by which a protein structure assumes its functional shape of conformation, and has been the subject of research since the publication of the first software tool for protein structure prediction. Protein folding in silico approaches this issue by introducing an ab initio model that attempts to simulate as far as possible the folding process as it takes place in vivo, and attempts to construct a mechanistic model on the basis of the predictions made. The opening chapters discuss the early stage intermediate and late stage intermediate models, followed by a discussion of structural information that affects the interpretation of the folding process. The second half of the book covers a variety of topics including ligand binding site recognition, the "fuzzy oil drop" model and its use in simulation of the polypeptide chain, and misfolded proteins. The book ends with an overview of a number of other ab initio methods for protein structure predictions and some concluding remarks. - Discusses a range of ab initio models for protein structure prediction - Introduces a unique model based on experimental observations - Describes various methods for the quantitative assessment of the presented models from the viewpoint of information theory
Protein Simulation focuses on predicting how protein will act in vivo. These studies use computer analysis, computer modeling, and statistical probability to predict protein function.* Force Fields* Ligand Binding* Protein Membrane Simulation* Enzyme Dynamics* Protein Folding and unfolding simulations
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.