Protein Simulations

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

Protein engineering endeavors to design new peptides and proteins or to change the structural and/or functional characteristics of existing ones for specific purposes, opening the way for the development of new drugs. This work develops in a comprehensive way the theoretical formulation for the methods used in computer-assisted modeling and predictions, starting from the basic concepts and proceeding to the more sophisticated methods, such as Monte Carlo and molecular dynamics. An evaluation of the approximations inherent to the simulations will allow the reader to obtain a perspective of the possible deficiencies and difficulties and approach the task with realistic expectations. Examples from the authors laboratories, as well as from the literature provide useful information.

Provides hands-on knowledge enabling students of and researchers in chemistry, biology, and engineering to perform molecular simulations This book introduces the fundamentals of molecular simulations for a broad, practice-oriented audience and presents a thorough overview of the underlying concepts. It covers classical mechanics for many-molecule systems as well as force-field models in classical molecular dynamics; introduces probability concepts and statistical mechanics; and analyzes numerous simulation methods, techniques, and applications. Molecular Simulations: Fundamentals and Practice starts by covering Newton's equations, which form the basis of classical mechanics, then continues on to force-field methods for modelling potential energy surfaces. It gives an account of probability concepts before subsequently introducing readers to statistical and quantum mechanics. In addition to Monte-Carlo methods, which are based on random sampling, the core of the book covers molecular dynamics simulations in detail and shows how to derive critical physical parameters. It finishes by presenting advanced techniques, and gives invaluable advice on how to set up simulations for a diverse range of applications. -Addresses the current need of students of and researchers in chemistry, biology, and engineering to understand and perform their own molecular simulations -Covers the nitty-gritty ? from Newton's equations and classical mechanics over force-field methods, potential energy surfaces, and probability concepts to statistical and quantum mechanics -Introduces physical, chemical, and mathematical background knowledge in direct relation with simulation practice -Highlights deterministic approaches and random sampling (eg: molecular dynamics versus Monte-Carlo methods) -Contains advanced techniques and practical advice for setting up different simulations to prepare readers entering this exciting field Molecular Simulations: Fundamentals and Practice is an excellent book benefitting chemist, biologists, engineers as well as materials scientists and those involved in biotechnology.

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Although computational modeling and simulation of material deformation was initiated with the study of structurally simple materials and inert environments, there is an increasing demand for predictive simulation of more realistic material structure and physical conditions. In particular, it is recognized that applied mechanical force can plausibly alter chemical reactions inside materials or at material interfaces, though the fundamental reasons for this chemomechanical coupling are studied in a material-speci c manner. Atomistic-level s- ulations can provide insight into the unit processes that facilitate kinetic reactions within complex materials, but the typical nanosecond timescales of such simulations are in contrast to the second-scale to hour-scale timescales of experimentally accessible or technologically relevant timescales. Further, in complex materials these key unit processes are “rare events” due to the high energy barriers associated with those processes. Examples of such rare events include unbinding between two proteins that tether biological cells to extracellular materials [1], unfolding of complex polymers, stiffness and bond breaking in amorphous glass bers and gels [2], and diffusive hops of point defects within crystalline alloys [3].

The need for information in the understanding of membrane systems has been caused by three things - an increase in computer power; methodological developments and the recent expansion in the number of researchers working on it worldwide. However, there has been no up-to-date book that covers the application of simulation methods to membrane systems directly and this book fills an important void in the market. It provides a much needed update on the current methods and applications as well as highlighting recent advances in the way computer simulation can be applied to the field of membranes and membrane proteins. The objectives are to show how simulation methods can provide an important contribution to the understanding of these systems. The scope of the book is such that it covers simulation of membranes and membrane proteins, but also covers the more recent methodological developments such as coarse-grained molecular dynamics and multiscale approaches in systems biology. Applications embrace a range of biological processes including ion channel and transport proteins. The book is wide ranging with broad coverage and a strong coupling to experimental results wherever possible, including colour illustrations to highlight particular aspects of molecular structure. With an internationally respected list of authors, its publication is timely and it will prove indispensable to a large scientific readership.

Machine learning methods such as neural networks, non-linear dimensionality reduction techniques, random forests and others meet in this research topic with biomolecular simulations. The authors of eight articles applied these methods to analyze simulation results, accelerate simulations or to make molecular mechanics force fields more accurate.

Information on our detailed genetic code is increasing at a dramatic pace. We need to understand how that is translated into the three-dimensional structure of proteins in order to make use of the information. Progress in this field is hampered by the lack of precise force fields and of efficient codes for finding equilibrium configurations of heteropolymers. However, there has been rapid advance in recent years, and this volume discusses that.