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This volume explores the recent advancements in biomolecular simulations of proteins, small molecules, and nucleic acids, with a primary focus on classical molecular dynamics (MD) simulations at atomistic, coarse-grained, and quantum/ab-initio levels. The chapters in this book are divided into four parts: Part One looks at recent techniques used in the development of physic-chemical models of proteins, small molecules, nucleic acids, and lipids; Part Two discusses enhanced sampling and free-energy calculations; Part Three talks about integrative computational and experimental approaches for biomolecular simulations; and Part Four focuses on analyzing, visualizing, and comparing biomolecular simulations. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and comprehensive, Biomolecular Simulations: Methods and Protocols is a valuable resource for both novice and expert researchers who are interested in studying different areas of biomolecular simulations, and discovering new tools to progress their future projects.
This textbook originated from the course 'Simulation, Modeling, and Computations in Biophysics' that I have taught at the University of Chicago since 2011. The students typically came from a wide range of backgrounds, including biology, physics, chemistry, biochemistry, and mathematics, and the course was intentionally adapted for senior undergraduate students and graduate students. This is not a highly technical book dedicated to specialists. The objective is to provide a broad survey from the physical description of a complex molecular system at the most fundamental level, to the type of phenomenological models commonly used to represent the function of large biological macromolecular machines.The key conceptual elements serving as building blocks in the formulation of different levels of approximations are introduced along the way, aiming to clarify as much as possible how they are interrelated. The only assumption is a basic familiarity with simple mathematics (calculus and integrals, ordinary differential equations, matrix linear algebra, and Fourier-Laplace transforms).
Over the past 40 years the field of molecular simulations has evolved from picosecond studies of isolated macromolecules in vacuum to studies of complex, chemically heterogeneous biological systems consisting of millions of atoms, with the simulation time scales spanning up to milliseconds. In Biomolecular Simulations: Methods and Protocols, expert researchers illustrate many of the methods commonly used in molecular modelling of biological systems, including methods for electronic structure calculations, classical molecular dynamics simulations and coarse-grained techniques. A selection of advanced techniques and recent methodological developments, which rarely find coverage in traditional textbooks, is also introduced. Written in the highly successful Methods in Molecular Biology series format, chapters include general introductions to well-established computational methodologies, applications to real-world biological systems, as well as practical tips and general protocols on carrying out biomolecular simulations. Special emphasis is placed on simulations of proteins, lipids, nucleic acids, and carbohydrates. Authoritative and practical, Biomolecular Simulations: Methods and Protocols seeks to aid scientists in further simulation studies of biological systems.
A guide to applying the power of modern simulation tools to better drug design Biomolecular Simulations in Structure-based Drug Discovery offers an up-to-date and comprehensive review of modern simulation tools and their applications in real-life drug discovery, for better and quicker results in structure-based drug design. The authors describe common tools used in the biomolecular simulation of drugs and their targets and offer an analysis of the accuracy of the predictions. They also show how to integrate modeling with other experimental data. Filled with numerous case studies from different therapeutic fields, the book helps professionals to quickly adopt these new methods for their current projects. Experts from the pharmaceutical industry and academic institutions present real-life examples for important target classes such as GPCRs, ion channels and amyloids as well as for common challenges in structure-based drug discovery. Biomolecular Simulations in Structure-based Drug Discovery is an important resource that: -Contains a review of the current generation of biomolecular simulation tools that have the robustness and speed that allows them to be used as routine tools by non-specialists -Includes information on the novel methods and strategies for the modeling of drug-target interactions within the framework of real-life drug discovery and development -Offers numerous illustrative case studies from a wide-range of therapeutic fields -Presents an application-oriented reference that is ideal for those working in the various fields Written for medicinal chemists, professionals in the pharmaceutical industry, and pharmaceutical chemists, Biomolecular Simulations in Structure-based Drug Discovery is a comprehensive resource to modern simulation tools that complement and have the potential to complement or replace laboratory assays for better results in drug design.
Molecular dynamics simulations have become instrumental in replacing our view of proteins as relatively rigid structures with the realization that they were dynamic systems, whose internal motions play a functional role. Over the years, such simulations have become a central part of biophysics. Applications of molecular dynamics in biophysics range over many areas. They are used in the structure determination of macromolecules with x-ray and NMR data, the modelling of unknown structures from their sequence, the study of enzyme mechanisms, the estimation of ligand-binding free energies, the evaluation of the role of conformational change in protein function, and drug design for targets of known structures. The widespread application of molecular dynamics and related methodologies suggests that it would be useful to have available an introductory self-contained course by which students with a relatively limited background in chemistry, biology and computer literacy, can learn the fundamentals of the field. This Guide to Biomolecular Simulations tries to fill this need. The Guide consists of six chapters which provide the fundamentals of the field and six chapters which introduce the reader to more specialized but important applications of the methodology.
This book is the third volume in this highly successful series. Since the first volume in 1989 and the second in 1993, many exciting developments have occurred in the development of simulation techniques and their application to key biological problems such as protein folding, protein structure prediction and structure-based design, and in how, by combining experimental and theoretical approaches, very large biological systems can be studied at the molecular level. This series attempts to capture that progress. Volume 3 includes contributions that highlight developments in methodology which enable longer and more realistic simulations (e.g. multiple time steps and variable reduction techniques), a study of force fields for proteins and new force field development, a novel approach to the description of molecular shape and the use of molecular shape descriptors, the study of condensed phase chemical reactions, the use of electrostatic techniques in the study of protonation, equilibria and flexible docking studies, structure refinement using experimental data (X-ray, NMR, neutron, infrared) and theoretical methods (solvation models, normal mode analysis, MD simulations, MC lattice dynamics, and knowledge-based potentials). There are several chapters that show progress in the development of methodologies for the study of folding processes, binding affinities, and the prediction of ligand-protein complexes. The chapters, contributed by experienced researchers, many of whom are leaders in their field of study, are organised to cover developments in: simulation methodology the treatment of electrostatics protein structure refinement the combined experimental and theoretical approaches to the study of very large biological systems applications and methodology involved in the study of protein folding applications and methodology associated with structure-based design.
This two volume set describes innovations in biomolecular modeling and simulation, in both the algorithmic and application fronts.
Published continuously since 1944, the Advances in Protein Chemistry and Structural Biology series is the essential resource for protein chemists. Each volume brings forth new information about protocols and analysis of proteins. Each thematically organized volume is guest edited by leading experts in a broad range of protein-related topics. - Describes advances in biomolecular modelling and simulations - Chapters are written by authorities in their field - Targeted to a wide audience of researchers, specialists, and students - The information provided in the volume is well supported by a number of high quality illustrations, figures, and tables
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.
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.